Data Engineer

Develop and optimize complex PostgreSQL queries, views, indexes, functions, and stored procedures.

Analyze query execution plans and resolve database performance issues.

Design and maintain hierarchical data structures; develop safe schema migration, seed-data, and data-correction scripts.

Support database schema evolution across development, test, and production environments.

Build and maintain integrations between SyncPoint and external government and commercial systems including Navy ERP, PIEE, and EDW.

Develop transformations between external schemas and SyncPoint’s internal canonical data models.

Support secure service-to-service REST API integrations with appropriate authentication and authorization patterns.

Prepare trusted, structured datasets for AI, machine-learning, and analytics capabilities.

Support development of Retrieval-Augmented Generation (RAG) capabilities and data retrieval services for generative AI workflows.

Work with the AI/ML Engineer to establish data selection, metadata, provenance, lineage, and access-control requirements.

Ensure AI systems retrieve only information the requesting user or service is authorized to access.

Establish automated data-quality checks for completeness, validity, consistency, uniqueness, and referential integrity.

Maintain data lineage and traceability for critical financial information; document data mappings, transformation rules, and data dictionaries.

Support data retention, archival, and deletion requirements appropriate to DoD and compliance environments.

Design data solutions appropriate for DoD Impact Level 4 (IL4) environments.

Support secure handling and protection of Controlled Unclassified Information (CUI).

Apply least-privilege access, encryption, auditing, and secure data-transfer practices.

Ensure development and troubleshooting processes do not expose protected data through logs, development tools, or unauthorized environments.

Strong data modeling and SQL expertise

Data pipeline design, development, and reliability

Security-conscious data engineering

Ability to translate business requirements into durable data models

Systems-level problem solving across distributed data flows

Clear technical documentation

Effective collaboration with architects, developers, DevOps, and AI/ML engineers

Technical Environment: Databases: PostgreSQL, Azure Cosmos DB Cloud: Microsoft Azure / Azure Government Languages: SQL, C#/.NET, Python Data Engineering: ETL/ELT, data modeling, data quality, JSON, REST APIs Messaging: RabbitMQ, Azure Service Bus, Azure Event Bus Architecture: Microservices, event-driven, domain events, data projections AI/Data Services: Azure OpenAI, embeddings, vector retrieval, RAG DevOps: Git, Docker, CI/CD, Kubernetes, Azure DevOps Security: Managed Identity, RBAC/ABAC, private networking, CUI/IL4 controls REQUIRED EXPERIENCE:

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, or a related technical discipline, or equivalent professional experience.

5+ years of professional experience in data engineering, database engineering, or backend engineering.

Advanced proficiency with SQL and relational database design.

Strong hands-on experience with PostgreSQL, including schema design, query optimization, and performance tuning.

Experience building production ETL/ELT pipelines.

Experience with C#/.NET for data processing, integration, or automation.

Experience developing or consuming REST APIs.

Experience with cloud-based data platforms, preferably Microsoft Azure.

Strong understanding of data quality, lineage, auditing, and governance principles.

Experience with Git-based development workflows and CI/CD practices.

Experience with Azure Government.

Experience developing solutions for DoD or other federal government environments.

Familiarity with IL4/IL5, CUI, NIST 800-171, or related compliance requirements.

Experience with event-driven architectures (RabbitMQ, Azure Service Bus, Azure Event Hubs, or Kafka).

Experience with microservice architectures and eventual-consistency patterns.

Experience integrating financial, ERP, planning, or program-management systems.

Experience with large-scale legacy data migrations.

Experience supporting AI/ML or generative AI applications; familiarity with vector search, embeddings, or RAG architectures.

Experience with Azure Cosmos DB.