Analytics Engineer

• Perform knowledge elicitation from customer subject matter experts and convert that to build analytic solutions
• Design, engineer, and optimize sustainment of large-scale distributed computation platforms and supporting environment (ecosystems) for various stakeholders, business owners, and industry partners
• Oversee the transition of services from third-party vendors to the analytic environment and be responsible for ad hoc and formal end-user training
• Identify applicable data to perform analytics and create solutions to acquire, transform, and load or correlate data components to and from the analytic environment
• Develop custom data modeling procedures to assist with data mining, modeling, and production
• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• Develop processes and tools to monitor and analyze model performance and data accuracy
• Interpret and communicate results to non-technical customers

Data Mining & Analytics Engineer, Journeyman – Security Clearance Required

• Perform knowledge elicitation from customer subject matter experts and convert that to build analytic solutions
• Design, engineer, and optimize sustainment of large-scale distributed computation platforms and supporting environment (ecosystems) for various stakeholders, business owners, and industry partners
• Manage teams of system administrators, prioritize work, identify high-risk critical problems, and dedicate appropriate resources
• Oversee the transition of services from third-party vendors to the analytic environment and be responsible for ad hoc and formal end-user training
• Identify applicable data to perform analytics and create solutions to acquire, transform, and load or correlate data components to and from the analytic environment
• Develop custom data modeling procedures to assist with data mining, modeling, and production
• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• Develop processes and tools to monitor and analyze model performance and data accuracy
• Interpret and communicate results to non-technical customers

Senior Data Mining & Analytics Engineer, Security Clearance Required

• Access, query, and extract data from VHA enterprise systems and files including CDW, VistA, VSSC, RAMP, PTF (MedSAS), MCA System, PCMM, NPCD, and the VETSNET Corporate Mini Master File to support programmatic reporting and analysis.
• Develop and apply advanced computerized models and algorithms to identify, extrapolate, and validate data patterns that support Specialty Care Program Office decision-making and future business trend forecasting.
• Design and produce clear, accurate data visualizations including graphs, charts, dashboards, and summary reports that translate complex mathematical and statistical information into accessible formats for program managers and leadership.
• Present analytical findings and data-driven recommendations to program managers and senior stakeholders, advising on how to best adjust business models and operational strategies to achieve favorable programmatic outcomes.
• Ensure data integrity, consistency, and accuracy across multiple VHA data sources by performing routine data validation, reconciliation, and quality assurance reviews in support of ongoing and ad hoc reporting requirements.
• Collaborate with VHA Specialty Care Program Office staff and other stakeholders to define data requirements, document analytical methodologies, and maintain standardized reporting processes in accordance with federal data governance and contracting standards.

Specialty Care Data Management and Analytics Support Specialist

• Consult with teams across the organization to translate key product and business processes into technical data requirements. Use dbt, BigQuery, and SQL to build up Packback’s metrics layer to enable self-serve access to core analytics.
• Build, optimize, and orchestrate data pipelines with dbt, Airflow, and Python
• Establish data integrity standards and SLAs to ensure timely, accurate delivery of data
• Build insightful and reliable dashboards to track performance of core company metrics across the product and business
• Collaborate with business operations teams to define and train on best practices with respect to data modeling, analytics, and visualization
• Collaborate with leadership to conduct analyses and apply statistical methods to answer day-to-day questions or support larger initiatives
• Work within Packback’s research function with partner institutions and perform in-depth analyses to understand how Packback’s products are driving key student outcomes
• Consult on the adoption of new technologies that impact Packback’s data infrastructure

• Build, automate, and operate enterprise analytics platforms using Terraform, GitHub, Kubernetes, and GitOps to create secure, repeatable, and scalable cloud environments.
• Develop next-generation analytics infrastructure by modernizing legacy deployments and implementing hardened CI/CD workflows aligned with Zero Trust and cloud governance best practices.
• Create reusable modules, templates, and reference architectures to help product teams move faster and strengthen platform standardization.
• Integrate and operationalize third-party libraries, APIs, and partner technologies across end-to-end cloud solutions.
• Support engineering excellence through code commits, PR reviews, automation improvements, and enhanced platform observability.
• Improve containerized workloads across Azure and AWS, and increase efficiency on analytic platforms such as Databricks, Posit Workbench, and Posit Connect.
• Collaborate closely with IT and security organizations to help ensure compliance, resiliency, and policy alignment.
• Leverage tools such as GitHub, Jira, and ServiceNow as part of a mature DevSecOps operating model.

Full Stack DevOps Engineer

• support client enterprise ETL environment
• lead and assist with the transition from Informatica to Oracle Data Integrator (ODI)
• designing, developing, enhancing, testing, and deploying ETL solutions
• migrating existing Informatica workflows to ODI
• troubleshooting and maintaining ETL processes across Development, Test, and Production environments
• administering the ETL platform while ensuring compliance with client cybersecurity, data governance, and operational standards

Data Integration Engineer – ETL Developer

• Support the design, development, testing, and maintenance of dashboards, reports, workflows, and data products.
• Build Power BI dashboards and reports to support acquisition, contract writing, workload, data quality, and leadership reporting needs.
• Support Power Platform development, including Power Apps and Power Automate workflows.
• Assist with Palantir Foundry development, including datasets, transformations, dashboards, applications, and analytical products.
• Work within Advana and Jupiter environments to access, explore, analyze, and prepare data.
• Use Databricks, SQL, Python, PySpark, or similar tools to clean, transform, validate, and prepare data for analytics and AI use cases.
• Support AI-enabled analytics capabilities, including automated insights, natural language querying, anomaly detection, trend analysis, and leadership summaries.
• Validate AI-generated insights against source data and business rules.
• Document data sources, transformation logic, assumptions, business rules, calculations, and known data limitations.
• Assist with data quality checks, data reconciliation, and issue identification.
• Support user testing, dashboard validation, prototype development, and stakeholder feedback sessions.
• Work with acquisition and contract writing subject matter experts to understand reporting needs and business context.
• Support recurring reporting, ad hoc analysis, and executive-level data requests.
• Collaborate with the lead engineer, business analysts, system owners, and client stakeholders to deliver timely and accurate analytics products.

AI & Data Analytics Developer – Government Clearance Eligible

• Lead the design, development, and delivery of AI-enabled analytics products supporting acquisition and contract writing operations.
• Build and maintain data products, dashboards, workflows, and analytical applications using Palantir Foundry and Microsoft Power Platform.
• Work within Advana and Jupiter environments to access, analyze, and connect relevant data sources to Palantir Foundry and Power Platform solutions.
• Develop data pipelines, reusable data models, and analytics layers using Databricks, SQL, Python, PySpark, or similar tools.
• Build and maintain ETL/ELT pipelines in Foundry’s Pipeline Builder and Code Repositories — from raw ingest through staging to curated, production-ready datasets.
• Design end-to-end big data architectures across cloud implementations of Foundry, including data lakes, pipelines, warehouses, and analytics platforms; apply Foundry’s open architecture principles to ensure interoperability with existing IT systems and meet organizational and compliance requirements.
• Integrate AI, machine learning, natural language processing, generative AI, or automated insight-generation capabilities into analytics products and workflows.
• Identify, prioritize, and drive analytics and AI use cases from concept through delivery.
• Partner with acquisition, contracting, program, and technical stakeholders to understand business problems and translate them into data and AI solutions.
• Develop AI-enabled capabilities such as natural language querying, automated leadership summaries, risk indicators, anomaly detection, trend analysis, workload forecasting, and decision-support recommendations.
• Build dashboards and reports that provide insight into contract writing activity, workload, procurement status, cycle times, data quality, system adoption, bottlenecks, and operational risk.
• Support data integration across contract writing, procurement, financial, program, and operational data sources.
• Validate AI-generated outputs against source data, business rules, and subject matter expert feedback.
• Establish standards for data quality, governance, documentation, and responsible AI use.
• Provide technical direction to junior or support-level data analytics staff.
• Present findings, prototypes, dashboards, and recommendations to both technical and non-technical stakeholders.

Lead AI and Data Analytics Engineer

• Architect, build and maintain efficient and reliable data products (dbt models, pipelines, Looker explores, visualizations, etc.) that enable data driven decision making.
• Build and maintain ELT pipelines from source systems to data warehouses.
• Influence strategy and drive execution of our analytical roadmap delivering self-service business intelligence at scale.
• Provide leadership and mentorship to other engineers fostering collaboration, knowledge sharing and a high bar for quality.
• Improve end users trust and confidence by driving best practices with regards to data discoverability, observability, lineage and stewardship.
• Contribute towards a robust data security strategy protecting sensitive information and content.
• Solve critical business problems through the application of programming, optimization, automation, and analytical skills.
• Drive functional strategy for AI adoption, identifying transformational opportunities that create competitive advantage in how we build and scale our data products.
• Build scalable AI-powered systems that fundamentally change how analytical work gets done across multiple teams.
• Serve as a trusted advisor to leadership on AI capabilities, limitations, and strategic implications for our data platform.
• Establish governance frameworks and best practices for responsible AI usage at scale within the analytics function.
• Transform core data and analytics processes through strategic AI integration—including intelligent pipeline monitoring, automated data quality checks, and AI-assisted insight generation.
• Quantify AI impact on key data metrics and make data-driven recommendations for continued investment.

Senior Analytics Engineer

• Design and develop data serving and semantic layers to support business needs ranging from traditional reporting to reverse ETL and LLM/AI implementations.
• Develop data models for use by analysts and applications from across the business using modern dimensional modeling practices to efficiently serve accurate, consistent data.
• Build and maintain robust, scalable data pipelines to extract, transform, and load (ETL, ELT) data from various sources into the data platform using both batch processing and event-driven patterns.
• Create efficient, performant data models to support business requirements and analytics needs.
• Implement and automate data quality checks and monitoring to ensure data accuracy and drive observability.
• Manage, troubleshoot and optimize existing data infrastructure, including cloud-based solutions and on-premises systems.
• Leverage cloud data platforms (Fabric, Databricks, Snowflake, etc.) for data storage, processing, and analysis.
• Work closely with data analysts, data scientists, and business stakeholders to understand their data needs and deliver solutions.
• Identify and resolve data-related issues and challenges for technical and non-technical stakeholders.
• Support company-wide projects ranging from server migrations to mergers and acquisitions as a data and systems expert.
• Automate data processes to improve efficiency and reduce manual effort.
• Implement modern concepts like metadata-driven pipelines and Infrastructure-as-Code that will play a key role in a scalable, resilient data platform.
• Document data processes, architecture, and workflows.

• Design and implement complex data pipelines and ETL processes to support cyber investigative capabilities across multi-classification domains
• Architect and develop ETL workflows for highly sensitive data in classified environments
• Support IC Data Services requirements by integrating various intelligence data sources and systems
• Develop and maintain data analytics solutions for desktop and web-based visual analytic applications
• Establish applications that produce manageable, actionable intelligence from streams of structured and semi-structured data
• Design strategies for enterprise database systems and set standards for operations, programming, and security
• Construct and optimize large relational databases across multi-enclave environments (Unclassified, Secret, and Top Secret)
• Tune performance of large-scale data workflows, ensuring cost efficiency, low latency, and high availability
• Design and manage Elasticsearch/Opensearch clusters for fast search, indexing, and retrieval of large-scale datasets
• Integrate new systems with existing warehouse structures and refine system performance and functionality
• Implement CI/CD pipelines for data systems, automate monitoring/alerting, and enforce infrastructure-as-code practices
• Provide technical leadership and mentorship to other team members
• Participate in Program Increments (PIs) and Agile Release Train (ART) activities

ETL Engineer – SME

• Design and implement advanced data visualizations and interactive dashboards that transform complex data into clear, actionable insights, applying strong user experience principles to drive understanding and data-driven decision-making.
• Lead the adoption and integration of Augmented Analytics capabilities, including AI/ML-driven insights, natural language query (NLQ), and natural language generation like “Talk to your Data” features within enterprise BI platforms.
• Lead and evolve self-service analytics (BIaaS) enablement frameworks, providing training, guidance, and reusable assets to empower business users and improve data literacy across the organization.
• Drive enterprise adoption and engagement through Analytics User Communities (Power BI/Tableau User Group etc.), incorporating feedback to continuously improve analytics capabilities and user experience.
• Own and manage the Analytics Service Catalog, ensuring user requests are fulfilled through standardized, governed, and scalable solutions aligned with enterprise priorities.
• Lead modernization efforts by migrating legacy BI assets to enterprise platforms (Power BI/Tableau), improving performance, scalability, and alignment with enterprise data strategy.
• Establish and maintain governance practices for visualization assets, including certification, reuse, lifecycle management, and adherence to data standards.
• Maximize the value of BI solutions by ensuring strong user engagement and platform reliability — tracking usage and performance, managing access/licensing, and providing proactive support to maintain solution integrity.
• Identify opportunities for optimization, automation, and innovation across analytics platforms, user experience, and data consumption patterns.
• Establish and enforce data visualization standards and best practices to ensure consistent, high-quality, user-centric analytics experiences across platforms.
• Provide subject matter expertise in BI and analytics, guiding Agile project teams with technical leadership to drive successful solution delivery.
• Mentor team members and others through Job Rotation/Shadow or skill up program and promote best practices in data visualization, storytelling, and analytics design.

Senior Data Visualization, Augmented Analytics Engineer

• Collaborate with stakeholders to understand business requirements and translate them into scalable and efficient data analytics solutions.
• Possess in-depth knowledge and hands-on experience with Microsoft Fabric ecosystem (Lakehouse, PySpark/SQL notebooks, data pipelines, and deployment pipelines).
• Understanding Microsoft Dynamics as a data source a big plus.
• Design data models that bridge the Fabric Lakehouse, Power BI semantic models, and reporting layers, ensuring consistency between raw, curated, and business-facing data.
• Optimize data models to support efficient data storage, retrieval, and analysis, ensuring data integrity, accuracy, and reliability.
• Knowledge of Fabric capacity (CU) optimization a big plus.
• Implement data integration pipelines using Microsoft Fabric and other relevant tools to extract, transform, and load data from various sources into a unified data platform.
• Create visually appealing and interactive dashboards, reports, and visualizations using Microsoft Power BI and DAX language, enabling users to gain valuable insights from data.
• Identify performance bottlenecks and implement optimizations to improve data processing, query performance, and overall system efficiency.
• Collaborate with cross-functional teams, providing technical leadership and guidance to data engineers, analysts, and other stakeholders to ensure successful project delivery.
• Keep abreast of the latest advancements in data analytics technologies (Microsoft based and others) and industry trends, continuously enhancing your expertise and applying best practices in solution design and implementation.

Analytics Engineer jobs in Virginia

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Data Mining & Analytics Engineer, Journeyman – Security Clearance Required

Senior Data Mining & Analytics Engineer, Security Clearance Required

Specialty Care Data Management and Analytics Support Specialist

Analytics Engineer

Full Stack DevOps Engineer

Data Integration Engineer – ETL Developer

AI & Data Analytics Developer – Government Clearance Eligible

Lead AI and Data Analytics Engineer

Senior Analytics Engineer

Analytics Engineer

ETL Engineer – SME

Senior Data Visualization, Augmented Analytics Engineer

Data Analytics Engineer