Data Engineer
SGA
Data Engineer
Software Guidance & Assistance, Inc., (SGA), is searching for a Data Engineer for a contract assignment with one of our premier regulatory clients in Rockville, MD or Tysons, VA. The Data Engineer works with moderate supervision across two equally weighted domains: (1) large-scale data pipeline development processing market events in a cloud environment, and (2) design and development of agentic AI systems including LLM-powered regulatory data assistants, MCP servers, and agent harness architectures. This position contributes to overall product quality throughout the software development lifecycle. Responsibilities include:
- Build and maintain ETL/ELT pipelines using Apache Spark, Hive, and Trino across S3-based data lake environments
- Develop and optimize SQL for large-scale surveillance datasets including window functions, multi-table joins, and complex aggregations
- Build and engineer big data systems (EMR-on-EC2, EMR-on-EKS) and develop solutions on analytical platforms (SageMaker, Domino, Dataiku)
- Participate in data quality monitoring, anomaly detection, and production incident investigation
- Develop AI agent systems using AWS Bedrock and agent frameworks (Strands Agents SDK, LangChain/LangGraph, or equivalent)
- Build agent harness architectures combining LLM reasoning with deterministic execution - skill/RAG-based SQL generation and structured output validation
- Implement agent memory, context management, and tool integration (MCP servers, API connectors, data catalog lookups) across the data lake
- Build evaluation frameworks for agent accuracy - paraphrase robustness, routing precision, and structural consistency
- Stay informed of advances in LLM frameworks (LangGraph, Google ADK, AWS Strands) and emerging AI capabilities
- Write clean, well-tested code; contribute to CI/CD Jenkins pipelines and infrastructure-as-code on AWS
- Ensure secure handling of RCI and sensitive regulatory data across both data pipelines and agent outputs - auditable execution traces
- Adhere to FINRA and team standards for secure development practices and technology policies
- Partner across teams, communicate technical information at the appropriate level, and maintain documentation on Confluence/Wiki
- Actively learn from senior team members; contribute to process improvement in line with FINRA's values of collaboration, expertise, innovation, and responsibility
Required Skills:
- Data Engineering & Big Data Technologies
- Experience building data pipelines using Apache Spark (PySpark preferred) and SQL
- Experience with SQL query engines (Hive, Trino/Presto, or similar) and cloud data platforms (AWS S3, EMR, Lambda)
- Real-world experience with debugging and mitigation strategies
- Generative AI & Agentic Systems
- Practical experience building LLM-powered agent systems that use tools and produce structured outputs (not just chatbot interfaces)
- Hands-on experience with at least one agent framework: LangChain, LangGraph, AWS Strands, or equivalent
- Working knowledge of prompt engineering, RAG architectures, and context/memory management
- Experience with foundation model APIs (Anthropic Claude, Amazon Nova, OpenAI, or similar)
- Memory Architecture: Understanding of agent memory tiers - working memory, episodic memory, semantic memory - and strategies for context persistence, pruning, and retrieval across sessions
- Agent Harness Design: Familiarity with harness patterns that wrap LLM reasoning with deterministic guardrails, tool routing, verification loops, and graceful degradation
- AI Tool Proficiency
- Hands-on experience with AI development tools (GitHub Copilot, Q Developer, ChatGPT, Claude, etc.)
- Experience with spec-driven development - using structured specifications to guide AI code generation, review, and validation
- Ability to leverage AI pair programming for code suggestions, debugging, refactoring, and automated test generation
- Cloud Technologies
- Experience with AWS services like S3, EMR, EMR on EKS, Lambda, Bedrock, Step Functions, etc.
- Hands-on experience using S3 with Spark (e.g., dealing with file formats, consistency issues)
- Familiarity with AWS Bedrock for foundation model invocation, knowledge bases, guardrails, and agent orchestration
- Exposure to Google Cloud Vertex AI (model garden, grounding, agent builder) or equivalent managed AI platforms
- Familiarity with AWS monitoring and logging tools (CloudWatch, CloudTrail) for production workloads
- Programming - Python
- Proficiency in Python for data engineering and automation
- Ability to write clean, modular, and performant code
- Experience with functional programming concepts (e.g., immutability, higher-order functions)
- Strong understanding of collections, concurrency, and memory management
- SQL Skills (Window Functions, Joins, Complex Queries)
- Proficiency with SQL window functions, multi-table joins, and aggregations
- Ability to write and optimize complex SQL queries
- Experience handling edge cases like NULLs, duplicates, and ordering
- Good to Have
- AWS Bedrock AgentCore (memory, identity, tool gateway)
- Model Context Protocol (MCP) server development and integration
- Agent evaluation harnesses and agentic patterns (draft-verification, compile-style generation)
- Fine-tuning foundation models for domain-specific tasks (LoRA, PEFT, or managed fine-tuning via Bedrock/Vertex AI)
- Local model execution with Ollama, vLLM, or similar for development and experimentation
- Vector databases (FAISS, Pinecone, OpenSearch)
- Docker, Kubernetes, and Amazon EKS for containerized workloads
- Infrastructure as Code (Terraform, CloudFormation)
- Experience with CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions, ArgoCD)
- Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack)
- AWS certifications (AI Practitioner, Solutions Architect, or Kubernetes certifications like CKA/CKAD)
- Education / Experience Requirements
- Bachelor's degree in Computer Science, Data Science, Information Systems, or related discipline with at least two (2) years of related experience; or equivalent training and/or work experience; past Financial Services industry experience preferred
- Demonstrated technical expertise in Object Oriented and database technologies/concepts which resulted in deployment of enterprise quality solutions
- Extensive knowledge of industry leading software engineering approaches including Test Automation, Build Automation and Configuration Management frameworks
- Strong written and verbal technical communication skills
- Demonstrated ability to develop effective working relationships that improved the quality of work products
- Ability to maintain focus and develop proficiency in new skills rapidly
- Ability to work in a fast paced environment
SGA is a technology and resource solutions provider driven to stand out. We are a women-owned business. Our mission: to solve big IT problems with a more personal, boutique approach. Each year, we match consultants like you to more than 1,000 engagements. When we say let's work better together, we mean it. You'll join a diverse team built on these core values: customer service, employee development, and quality and integrity in everything we do. Be yourself, love what you do and find your passion at work.
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