eSimplicity

QA Automation Engineer

• Implement and administer CI/CD pipelines for all ETL and data platform deliverables using CloudFormation templates, GitHub-based version control, and AWS Service Catalog, enabling successful builds and deployments to staging and production with a single command.
• Manage cloud-based infrastructure and services using approved Infrastructure-as-Code methodologies, Immutable Architecture principles, and reproducible deployment processes across development, staging, and production environments.
• Embed quality and security gates into CI/CD decision points, including static code analysis, dependency analysis, and government-provided container analysis tools; support remediation of medium- and high-level static and dynamic vulnerabilities in alignment with OWASP ASVS 4.0, Level 2.
• Automate orchestration and scheduling of data retrieval and ingestion jobs using Amazon Managed Workflows for Apache Airflow (MWAA), AWS Glue, Lambda, EventBridge, Step Functions, SNS, and SQS.
• Support release management, including Change Requests to the Change Control Board, release documentation, deployment references, rollback procedures, and project closeout within contract timelines.
• Ensure smooth operation of systems and infrastructure through monitoring, alerting, logging, preventative maintenance, and real-time remediation; keep production configurations consistent and controllable in support of ATO, FISMA, and NIST 800-53 compliance.
• Optimize system performance and cloud resource utilization to reduce cloud costs and deliver efficiency gains across the technical stack.
• Support disaster recovery exercises and actual events, ensuring production data loads continue as expected; provide pre-production deployment and data load support in lower environments.
• Provide on-call and after-hours support for production outages and emergencies as part of a team rotation, with full production support processes, documentation, and monitoring/alerting solutions.
• Leverage AI-assisted development tools to accelerate automation, improve code quality, and reduce operational burden while adhering to security and performance standards.
• Work as part of an integrated agile team, participating in sprint planning, program increment planning, and backlog refinement; support team performance dashboards (velocity, burn-down, code coverage, backlog traceability).

Platform Automation Engineer

QA Engineer

• Define test strategies, quality gates, and the Definition of Done for two-week agile delivery iterations; ensure releases meet government acceptance criteria before deployment.
• Develop and maintain comprehensive ETL Test Plans, test cases, test data, and validation criteria ensuring data pipelines are functionally correct, reliable, and meet business and data quality requirements.
• Lead adoption of automated testing frameworks, including unit, integration, and user-facing functional tests executed automatically through CI/CD, providing consistent protection against regressions.
• Manage code coverage measurement and progression toward the contract standard of a minimum 90% test coverage, with metrics visible in real-time dashboards.
• Coordinate Independent Verification & Validation (IV&V) and User Acceptance Testing (UAT) cycles; ensure findings are fully addressed and resubmitted within rapid contractual timelines and iteration counts stay within contract quality thresholds.
• Prepare Corrective Action Plans (CAPs) when performance standards are not met; ensure defects are logged, prioritized, triaged, and resolved in collaboration with engineering.
• Ensure complete, accurate release documentation accompanies every staging and production release, including approved test cases and results, data flow diagrams, architecture diagrams, and all artifacts required by the program's ETL standards.
• Verify data quality standards, including complete record and field loads, XSD validation where required, duplicate load prevention, and Data Steward-approved quality checks (e.g., AWS Glue data quality facilities).
• Integrate static code analysis, dependency scanning, and security scans into the Definition of Done; support delivery of code free of medium- and high-level vulnerabilities (OWASP ASVS 4.0, Level 2).
• Support periodic load and performance testing and validate results against acceptance criteria.
• Track quality metrics and provide regular status reporting on quality, risks, and release readiness to the Product Owner and program leadership.
• Support timely, accurate responses to data engineering customer inquiries and tickets in accordance with program service standards.
• Collaborate with Product Owners, Data Officers, IV&V teams, and developers to align QA practices with the program's enterprise ETL standards and drive their continuous improvement.

Senior Quality Assurance Engineer

Data Engineer

• Design, develop, ingest, and maintain well-architected data pipelines that retrieve data from external feeds (APIs, SFTP, HTTPS, FTP, web scraping, Direct Connect) and internal agency sources into the data lake landing zone and downstream curated zones.
• Develop production-grade ETL workflows using AWS Glue, PySpark, Python, Lambda, and EMR, integrated with a shared ETL common library and orchestrated via Amazon Managed Workflows for Apache Airflow (MWAA).
• Load data accurately and optimally into S3 zones (Parquet, ORC, Iceberg), relational datastores (PostgreSQL, Redshift, Oracle), NoSQL databases, and knowledge bases/vector stores, preventing duplicate loads and maintaining data integrity and traceability across all lifecycle stages.
• Implement schema enforcement, XSD validation, data quality checks, error handling, and automated SNS notifications; ensure all production jobs populate ETL Load Reports and Gap Reports through static and dynamic ETL metadata.
• Develop semantic-layer objects (tables, views, materialized views) that ensure complete data coverage, optimized query performance, and consistent application of business logic.
• Develop XML parsing/shredding logic for high-volume regulatory filings using Glue PySpark, supporting schema evolution and batch processing per program standards.
• Design pipelines with query performance in mind and support rollback, reload, and date-range reprocessing capabilities without manual intervention.
• Support self-service ETL development by other agency teams through standardized, reusable components aligned with program standards, and facilitate the transition of externally developed ETL jobs into the Data Engineering team's production support.
• Create and maintain required engineering artifacts, including business requirements, ETL design documents, mapping documents, data models, data dictionaries, deployment references, operations and maintenance guides, and test plans.
• Deploy code through automated CI/CD pipelines using CloudFormation templates, following agency release, security, and governance processes.
• Provide operational support for production jobs, including rapid identification and resolution of failed jobs and performance issues; participate in on-call/after-hours support for production outages and emergencies as part of a team rotation.
• Collaborate with Data Officers, Data Stewards, SMEs, data providers, and IV&V teams to understand requirements and deliver user-accepted solutions; engage closely with the Product Owner and cross-functional teams to provide timely updates and resolve issues.
• Leverage AI-assisted development tools to accelerate coding, optimize workflows, and enhance code quality while adhering to security and performance standards.
• Work in Agile teams; drive iterative delivery, joint problem-solving, and continuous improvement, including participation in sprint planning and program increment planning.

Strategy

• Serve as the CIO’s Deputy, representing the technology organization in leadership discussions, stakeholder engagements, and cross-functional decision-making with the authority to act on the CIO’s behalf.
• Own and drive solution strategy across all business units by developing strategic technical approaches and innovation roadmaps, leveraging existing domain knowledge while actively building expertise in mission areas where gaps exist.
• Work both in collaboration with the CIO and BD/Program teams and independently as the strategy lead.
• Participate in solution development without owning the architectural design.
• Lead and develop the staff organization across multiple teams through a combination of direct reports and dotted-line collaboration, conducting regular 1:1s, career development conversations, and performance management.
• Translate the CIO’s technical direction and strategic vision into actionable plans, priorities, and execution roadmaps across the technology organization.
• Drive people leadership at scale, including hiring, onboarding, mentoring, and retaining top talent while fostering a culture of accountability, curiosity, and continuous improvement.
• Own process leadership across the technology organization, establishing and refining operational cadences, decision frameworks, and communication rhythms that keep teams aligned and unblocked.
• Lead solution-oriented thinking across business units, ensuring teams deliver strategies and solutions that meet mission needs, drive competitive differentiation, and position eSimplicity for growth.
• Serve as an active listener and trusted advisor across the organization by hearing team concerns, synthesizing ground-level feedback, and ensuring leadership decisions are informed by real context.
• Communicate technical strategy, solution direction, and organizational priorities to diverse audiences, including engineers, executives, and government agency leadership, with clarity and compelling narrative.
• Coordinate cross-program and cross-agency strategy initiatives, applying and growing domain knowledge across areas such as data integration in defense environments, claims analytics and policy development at CMS, and citizen services modernization to ensure consistent and informed solution approaches across all programs.
• Identify operational risks, resource constraints, and organizational gaps before they become blockers, and drive resolution proactively.
• Partner with BD/Growth and Capture teams to lead or co-lead solution strategy for new opportunities, shaping technical volumes and ensuring delivery readiness for awarded contracts.
• Build and maintain organizational health metrics, tracking team engagement, delivery velocity, retention, and capacity to inform leadership decisions.
• Perform other duties as assigned.

VP, Chief of Solution Strategy

Engineer

• Assist with Performance Tuning: collaborating with a senior engineer, assist in analyzing and tuning Spark/PySpark and AWS Glue job performance (including partitioning, clustering, batch sizing, and file format optimization such as Parquet, ORC, Iceberg)
• Support Query Optimization: help optimize query performance across Athena, Trino, PostgreSQL, Redshift, and semantic-layer objects contributing to the efficient execution of user queries, reports, and dashboards
• Collaborative Troubleshooting: assist in identifying, diagnosing, and resolving failed production jobs and performance bottlenecks
• Support Performance Testing: participate in periodic load and performance tests; assist in defining benchmarks, documenting/analyzing results, and drafting test reports with recommendations for system improvements
• Pipeline Monitoring: monitor pipeline health using CloudWatch, ETL metadata, log analysis, and dashboards; assist in hardening/optimizing error handling and automated job notifications
• Team Collaboration: coordinate with developers, testers, and stakeholders to resolve technical issues; participate actively in agile ceremonies and Program Increment planning events
• Production Operations Support: work as part of a team to support production operations across a large data pipeline portfolio

Associate Performance Engineer

Program Manager

• Provide executive accountability for program performance, strategic alignment, contract and budget governance, stakeholder escalation, and overall delivery health.
• Lead an integrated, multi-team delivery model that maintains coverage across platform foundations, cloud operations, security, data supply chain, metadata, governed data asset operations, analytics experience, dashboard governance, public-facing products, AI and advanced platform enablement, external exchange, APIs, partner integrations, user success, documentation, and change management.
• Maintain a highly collaborative operating model that gives customer personnel continuous visibility into code, documentation, backlogs, metrics, dashboards, risks, decisions, and operational status in approved systems of record.
• Oversee program deliverables and management artifacts, including roadmap and PI Planning packages, monthly status, risk, and performance reporting, quality inputs, staffing and retention information, transition-in and transition-out readiness, and continuity planning.
• Provide leadership over applicable coverage areas, including cross-cutting program leadership, architecture coordination, product management, engineering operations, data operations, support operations, domain expertise, and enterprise stakeholder engagement.
• Promote reuse, portability, documentation quality, customer ownership of artifacts, and sustainable operations across code, infrastructure, analytics products, runbooks, AI configurations, metadata, service guides, and transition materials.
• Serve as the primary interface to client leadership, product owners, and security stakeholders, cloud and platform partners, product teams, and directed policy or operations groups owning stakeholder escalation and maintaining a collaborative, responsive, and trusting relationship.
• Collaborate with government partners on the strategic direction of the program, confirming alignment with agency data strategy imperatives and measurable progress toward program goals.
• Ensure program management practices make outcomes measurable across service reliability, data quality, delivery flow, engineering health, security and compliance, user success, analytics adoption, cost transparency, AI services, AIOps, and metadata maturity.
• Foster a badge-less culture of innovation and continuous improvement, driving cross-functional team success and coordinating across related programs and platform teams.

Program Director

Product Manager

• Define the product or team's vision within the scope of a particular team, product or feature set, ensuring alignment with user needs and business objectives
• Develop a clear perspective on future goals and definitions of success for the team/product and actively contribute to developing the long-term product vision and approach
• Develop expertise in the policies, operations, and targeted outcomes enabled by the team's work; Build a deep understanding of user needs, behaviors, and pain points that guide product strategy and decision-making
• Interface with Federal customers, end users, and Human-centered Design (HCD) researchers to identify and validate user and business needs
• Understand the scope of the enabler work and collaborate with System Architects, SMEs, Engineers, and others to assist with product planning and decision-making
• Understand, visualize, and manage upstream/downstream dependencies
• Prepare for and Participate in Quarterly (PI) Planning
• Support and lead Agile ceremonies (including planning, refinement, retrospectives, and standups)
• Develop actionable and value-driven features and stories, working with the team to define benefit hypothesis and acceptance criteria
• Collaborate with the development and testing team to ensure the implementation of the system tests
• Provide operational, tactical, and strategic inputs to accomplish program goals, meet planned deliverables, and exceed user satisfaction
• Drive delivery and continuous improvement by utilizing feedback and metrics to identify areas of opportunity
• Provide proactive and open communication across the program and stakeholders for transparency and awareness of progress and impediments
• Bridges the communication between the agile/project teams and key stakeholders by building and maintaining relationships.

Lead Product Manager

• Own roadmap development, intake-to-prioritization governance, user and stakeholder alignment, value measurement, and sequencing of cross-team product work.
• Develop and maintain thematic roadmaps that communicate how the program will deliver value in short-term and longer-term increments while remaining adaptable to funding, statutory, security, source-readiness, and policy changes.
• Partner with customer product owners and management stakeholders to define expected outcomes, hypotheses, value measures, trade-offs, and success criteria for features, workflows, data products, dashboards, APIs, and AI capabilities.
• Use user archetypes, journey research, support trends, and qualitative and quantitative feedback to guide product strategy, onboarding, documentation, service design, and AI rollout decisions.
• Coordinate product sequencing across delivery workstreams, including user success, documentation, support, analytics experience, dashboard governance, public-facing products, AI and platform feature enablement, data supply chain, metadata maturity, APIs, and partner integrations.
• Promote simple, intuitive, accessible user experiences across onboarding, access, discoverability, documentation, dashboards, conversational analytics, public-facing products, and support escalation paths.
• Lead applicable coverage areas, including unified front-door service, user support, onboarding, documentation, coaching and training, communications, analytics discoverability, dashboard governance, AI service rollout, support operations, and stakeholder engagement.

Principal Product Lead

Full-stack Engineer

• Lead engineering operations standards, CI/CD and release governance, SLO/SLI framework development, operational readiness criteria, DevSecOps practices, and reliability across the delivery model.
• Provide leadership for applicable technical coverage areas, including cloud infrastructure, infrastructure as code, CI/CD, source control, identity and access, observability, security automation, API runtime operations, security assessment support, remediation tracking, access reviews, vulnerability response, FedRAMP or comparable security alignment, and support escalation practices.
• Implement DevSecOps principles across the lifecycle, including iterative delivery, continuous integration and deployment, security shifted left, security by design, automated security testing, continuous monitoring, cross-functional collaboration, and continuous improvement.
• Establish and maintain release readiness and completion criteria for platform, infrastructure, pipeline, API, dashboard, documentation, AI-enabled service, and security artifact work.
• Support automated testing expectations, including CI/CD-integrated unit, lint, smoke, functional, performance, accessibility, and security tests, with a target of at least 80 percent automated test coverage for code-based deliverables unless the customer approves an alternative.
• Drive observability and operational action paths for service health, incident trends, performance, deployment risk, platform reliability, security posture, support escalation, and runbook-based recovery.
• Coordinate with customer stakeholders and cloud or platform partners on cloud governance, architecture reviews, account governance, logging, backups, patching, vulnerability scanning, cost management, and approved cloud service use.
• Ensure engineering artifacts, code repositories, infrastructure-as-code modules, runbooks, dashboard definitions, CI/CD workflows, security evidence, and related materials are maintained in customer-accessible systems of record from day one.

Principal Engineering Lead

Architect

• Own reference architecture, cross-team technical standards, architecture governance and decision-making, interoperability patterns, and major technical trade-off analysis.
• Lead applicable technical coverage across cloud and DevSecOps engineering, data engineering, data governance and metadata specialization, BI and analytics development, AI/ML platform engineering, security engineering and compliance, API services, partner integrations, and domain architecture.
• Guide architecture for platform-first delivery, approved technology direction, infrastructure as code, governed data trust patterns, API-first reuse, secure data sharing, AI-enabled service patterns, public-facing dashboards, and transition-ready artifact management.
• Coordinate with customer stakeholders, cloud and platform partners, security and privacy stakeholders, data owners, product teams, and downstream consumers on architecture reviews, environment changes, source onboarding, integrations, public-facing releases, and major technical decisions.
• Develop and maintain architectural artifacts in customer-accessible systems, including reference architectures, decision records, diagrams, standards, runbooks, interface documentation, joint operating agreements, service guides, data-flow documentation, and transition materials.
• Evaluate new or materially changed services against security, privacy, accessibility, cost transparency, observability, operational readiness, metadata maturity, AI governance, portability, and reuse criteria.
• Support joint operating agreements and cross-platform coordination for source-system and downstream-system interfaces, ingestion lead times, schema and metadata changes, incident boundaries, release dependencies, security and privacy responsibilities, support handoffs, and transition responsibilities.
• Promote out-of-the-box, native, reusable, open-source-aware, and portable solutions while minimizing unnecessary proprietary dependencies and avoiding contractor-managed external data systems.

Principal Architect

Data Scientist

• Lead data strategy execution, data supply chain and metadata maturity leadership
• Oversee data platform operations, distributed processing, programming and query languages
• Operate and improve source onboarding, ingestion, transformation, data quality
• Advance the program’s data trust model
• Establish and monitor data quality and processing timeliness practices
• Coordinate with data owners and teams
• Ensure metadata maturity advances as a tracked, multi-year effort
• Support governed self-service analytics, certified dashboards, and secure data sharing

Principal Data Lead

Principal

• Lead the scaled agile delivery model across the program, including PI Planning coordination, cross-team cadence management, dependency and risk tracking, and delivery transparency to the customer.
• Ensure all teams can participate fully in agile practices, including two-week sprint delivery, quarterly Program Increment planning, backlog refinement, sprint planning, daily coordination, demos, retrospectives, and cross-team coordination forums.
• Coordinate with product, architecture, engineering, data, security, AI, analytics, and user success leaders to align team backlogs with PI objectives, roadmap priorities, delivery constraints, and customer decision needs.
• Maintain visibility into delivery flow, program risks, dependencies, impediments, decisions, and delivery health using customer-approved work management, documentation, collaboration, source control, and dashboarding tools.
• Support routine reporting of delivery and product metrics, including deployment frequency, lead time to change, mean time to restore, change failure rate, burndown, sprint performance, PI performance, velocity, deliverable timeliness, and deliverable quality.
• Facilitate regular demonstrations of working software, operational improvements, research findings, documentation improvements, dashboards, APIs, AI capabilities, and other demonstrable progress.
• Promote blameless retrospectives and continuous improvement across delivery quality, service quality, collaboration, supportability, operational resilience, testing, and release readiness.
• Lead agile coordination for applicable coverage areas, including cross-cutting program leadership, product management, engineering operations, architecture coordination, data operations, user success, support operations, and participation across all delivery workstreams.

Principal Agile Lead

• Lead data science work across structured and unstructured program data, including data collection, processing, cleaning, profiling, and preparation for analysis and modeling on a governed data platform.
• Design, develop, train, evaluate, and refine machine learning models and AI services, selecting appropriate algorithms and techniques for specific customer and mission needs.
• Support deployment, monitoring, and maintenance of model performance in cloud environments using model lifecycle management, model serving, vector search, model evaluation, and related MLOps tooling.
• Deliver capabilities across both program AI tracks: internal AI-enabled delivery acceleration (AI-assisted schema tagging, automated code review, documentation generation, ticket automation) and user-facing AI services for customer users and approved consumers (AI assistants, conversational analytics, document-grounded search, and approved retrieval-augmented generation services).
• Operate within the program’s AI governance intake and review process, registering all production and pilot AI use cases before deployment, routing managed endpoints through a governed AI gateway layer, and maintaining inference logging, PII guardrails, rate controls, and human oversight and escalation paths.
• Plan and conduct proofs of concept and capability-gate evaluations that assess accuracy, governance integration, cost, operational overhead, and alignment to customer policy before scaling new AI capabilities.
• Embed responsible AI and equity requirements into delivery, including algorithmic risk and impact assessments, bias testing across relevant demographic and programmatic subgroups, plain-language limitations and escalation paths, and periodic bias and drift re-review.
• Collaborate closely with ML engineers, data engineers, platform teams, and cross-functional partners to develop and maintain the infrastructure and governed cloud environment required for AI/ML operations.
• Create, maintain, and improve documentation for methodologies, code, assumptions, experiments, evaluation artifacts, and decisions, including documentation of AI tools within the software bill of materials (SBOM), to support reproducibility and governance review.
• Communicate technical findings, strategic vision, risks, tradeoffs, and business value to leadership and key stakeholders, and provide people-management support and day-to-day technical guidance to a team of 3–5 engineers.

Principal Data Scientist

DevOps Engineer

• Partner with the development team to implement secure engineering patterns, maintain secure CI/CD pipelines, and remediate vulnerabilities, including contributing code, configuration, pipeline changes, and infrastructure updates where appropriate.
• Design and maintain security gates for code quality, dependency scanning, container image scanning, secrets detection, infrastructure misconfiguration, and policy compliance.
• Support Kubernetes and container security for AWS EKS environments, including image hardening, admission controls, runtime monitoring, network policies, workload identity, secrets management, and least-privilege access patterns.
• Support controls for new tooling/integration usage, the handling of sensitive data, and access controls.
• Help define and enforce secure-by-default engineering standards across the application, infrastructure, and delivery pipeline.
• Help drive the move toward ATO and near-real-time compliance.
• Implement monitoring of production runtime environments for vulnerabilities and compliance drift and make security and compliance reporting available on demand.
• Translate security findings into actionable engineering work items in JIRA and support teams through remediation, validation, and closure.
• Identify, document, and communicate security risks tied to modernization efforts
• Monitor cloud environments using AWS tools
• Participates in Agile processes including daily standups, demos, retrospectives, and sprint planning
• Collaborates with a fully integrated Agile team to deliver continuous improvement to designs, processes, and standards

Senior DevSecOps Engineer

Learning and Development

• Analyzing learning needs
• Designing and developing training materials
• Delivering engaging learning experiences that build capability across the FPS2 program
• Combining expertise in instructional design, adult learning methodologies, and facilitation skills to improve performance and support strategic objectives