Doran Jones Inc.

Backend Engineer

• Reverse engineer legacy monolithic and n-Tier .NET applications to understand architecture, business rules, data flows, and integration points
• Analyze poorly documented systems to extract functional and non-functional requirements
• Produce current-state architecture diagrams, data flow models, and dependency maps
• Identify technical debt, architectural anti-patterns, and modernization risks
• Design target state architectures to decompose monolithic systems into modular services, including microservices where appropriate
• Define modernization strategies, including strangler patterns, phased migrations, or parallel-run approaches, to minimize business disruption
• Lead refactoring initiatives to improve maintainability, scalability, and performance
• Analyze legacy database schemas, stored procedures, and embedded business logic to inform modernization decisions
• Support data migration and transformation strategies during system transition
• Translate complex legacy findings into clear documentation for technical and non-technical stakeholders
• Partner with business SMEs to ensure technical designs align with operational workflows and compliance requirements

Senior .NET Modernization Architect

IT Support

• Support and operate enterprise IT infrastructure environments, ensuring performance, availability, and capacity
• Own day-to-day infrastructure operations across servers, virtualization, networking, and cloud platforms
• Partner with engineering, security, and business stakeholders to define infrastructure requirements
• Support infrastructure modernization initiatives, including data center optimization and cloud migration efforts
• Act as a senior escalation point during infrastructure incidents and participate in root-cause analysis
• Provide hands-on L2/L3 support during critical initiatives and high-impact incidents
• Design, document, and support backup, recovery, and disaster recovery solutions
• Plan and execute patching, upgrades, and lifecycle management activities
• Maintain infrastructure documentation, standards, and operational runbooks
• Manage hardware and software inventory, licensing, and vendor support agreements
• Participate in an on-call rotation and support after-hours activities when required

Senior IT Infrastructure – Operations Analyst

AI Engineer

• Design and develop backend services and APIs using Python to support data ingestion, transformation, analytics, and AI workflows
• Integrate applications with Databricks, Delta Lake, and cloud-native data services
• Support batch and streaming data pipelines, including orchestration, monitoring, and reliability
• Implement secure, scalable access patterns for curated healthcare data in alignment with payer data governance and compliance requirements
• Design and integrate solutions that leverage Large Language Models for data exploration, summarization, workflow automation, and decision support
• Partner with data science and platform teams to operationalize ML- and LLM-driven capabilities in production environments
• Contribute to modern web user interfaces that surface data, analytics, and AI-driven insights
• Apply modern UI design principles to ensure usability, accessibility, and clarity for technical and business users
• Integrate frontend components with backend APIs and services
• Collaborate with data architects, platform engineers, designers, and product owners to deliver end-to-end solutions
• Participate in design reviews, code reviews, and architectural discussions
• Contribute to agile delivery practices, including backlog refinement, sprint planning, and iterative delivery

Senior Software Engineer – Data, AI Platforms

Data Engineer

• Assess existing data and reporting environments to identify opportunities where automation can replace manual work
• Design and drive an automation-first data architecture that supports scalable modernization across multiple environments
• Define and implement repeatable patterns for modernizing legacy data pipelines, analytics workloads, and reporting systems
• Leverage AI-assisted and tool-based approaches to accelerate modernization while maintaining control and compliance
• Establish architectural guardrails to ensure modernization efforts are consistent, auditable, and reliable
• Partner closely with data engineering, platform, and delivery teams to translate architecture into executable solutions
• Stay actively involved in hands-on execution to validate designs and drive outcomes
• Provide clear technical direction and pragmatic decision-making throughout the modernization lifecycle

Senior Data Architect – Automation-Led Data Modernization

• Assess legacy data and reporting workloads to identify where automation replaces manual effort.
• Lead the migration of Informatica-based data workloads to Databricks, ensuring performance, reliability, and data integrity.
• Design and execute an automation-first modernization strategy for data pipelines, reporting systems, and analytics platforms.
• Apply tool-assisted and AI-assisted techniques to accelerate modernization while maintaining compliance and control.
• Build repeatable frameworks and patterns for: Data ingestion, transformation, and orchestration; Reporting and analytics modernization; Data validation, reconciliation, and quality controls.
• Establish governance to ensure modernization efforts are consistent, auditable, and scalable.
• Partner with distributed data teams to deploy and scale modernization patterns across environments.
• Provide hands-on technical leadership while remaining engaged in execution.

Senior Data Engineer – Data Architect, Automation-Led Modernization

• Lead automation-led modernization of legacy data and reporting platforms at scale.
• Drive operational automation, repeatable architecture, and AI-assisted tooling.
• Lead the migration of data pipelines and integrations from Informatica to Databricks.
• Build scalable, repeatable patterns used across states and teams.
• Hands-on, senior role with ownership across architecture, design, and execution.

Senior Data Engineer / Data Architect – Automation-Led Modernization

Engineer

• Analyze and interpret legacy COBOL batch programs running on IBM mainframes, including programs utilizing JCL, DB2, and VSAM.
• Understand and document functional logic, control flow, and data transformations to support modernization efforts.
• Review and validate automatically generated functional documentation for accuracy, completeness, and alignment with actual program behavior.
• Design and execute test cases to validate business logic and ensure output consistency between legacy and modernized systems.
• Compare Java program outputs against original COBOL program results to identify discrepancies.
• Collaborate with modernization and Java development teams to resolve mismatches and refine generated code.
• Participate in transformation quality assurance activities and contribute to continuous improvement of the modernization platform.

Mainframe Modernization Engineer

Business Intelligence Developer

• Analyze and reverse engineer an existing SSRS reporting estate, including RDLs, shared datasets, data sources, subscriptions, and dependencies.
• Extract and document report logic from SSRS, including parameters, expressions, grouping, drill-through behavior, subreports, conditional formatting, and embedded code.
• Translate SSRS datasets and T-SQL logic into Power BI solutions using Power Query, DAX, and optimized data models.
• Rebuild SSRS pixel-perfect reports as Power BI reports and dashboards or as Power BI paginated reports where strict layout fidelity is required.
• Partner with GenAI engineering teams to refine prompts, retrieval context, and guardrails that support accurate conversion of report definitions and business rules.
• Define and implement reporting governance standards, including naming conventions, certified datasets, semantic models, workspace structure, and documentation.
• Implement security and access controls in Power BI, including row-level security, workspace permissions, and data sensitivity labeling.
• Validate functional parity between SSRS and Power BI outputs through reconciliations, golden datasets, automated checks, and stakeholder sign-offs.
• Optimize reporting performance through SQL tuning, data model optimization, aggregation strategies, incremental refresh, and capacity planning.
• Support UAT, training, and adoption through user enablement, report catalogs, release notes, and post-migration stabilization.

SSRS / Power BI Engineer – Reporting Modernization

Technical Program Manager

• Lead end-to-end ERP migration programs, including planning, execution, risk management, and delivery oversight.
• Drive program governance, including status reporting, milestones, dependencies, and executive communications.
• Coordinate and manage multiple cross-functional workstreams (technology, business, vendors, and external partners).
• Own program artifacts: program plans, RAID logs, budgets, timelines, and reporting dashboards.
• Partner closely with senior stakeholders to align delivery with business objectives.
• Identify and proactively mitigate risks and issues impacting scope, schedule, or quality.
• Ensure adherence to program management best practices and SDLC methodologies.
• Support change management and communication efforts related to ERP transformation initiatives.

Senior Technical Program Manager – ERP Migration

• Design, build, and deploy autonomous or semi-autonomous agents using industry-leading platforms such as Agno, CrewAI, LangGraph, or AutoGen.
• Create and manage sophisticated agent workflows that integrate LLMs, persistent memory, external tools, and multi-step decision logic.
• Develop bespoke Python-based components and tools to extend the capabilities of existing agent frameworks.
• Build and maintain scalable backend services, ensuring AI components are seamlessly integrated into enterprise-level architectures.
• Partner with product and data teams to define functional requirements and validate the efficacy of AI-driven features.
• Continuously monitor and improve the performance, reliability, and cost-efficiency of GenAI workloads and API usage.
• Stay at the forefront of the rapidly evolving GenAI and agentic AI landscape to implement best practices.