Data Engineer – Level III
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Job Description
Data Architect / Engineering Lead guiding AWS modernization, enterprise data platforms, and AI/ML enablement. Supporting AttainX’s federal NRCS technology programs under the USDA OMNI contract.
Responsibilities:
- Provide technical leadership for data architecture, data engineering, database modernization, and AI/ML enablement across the NRCS IT ecosystem
- Guide transformation of legacy SQL Server environments, SSIS-based ETL pipelines, and cross-database dependencies into scalable AWS cloud-native architectures
- Coordinate with the Enterprise Lead Architect, Government Program Managers, and cross-functional delivery teams under the OMNI contract
- Define and maintain data architecture standards, patterns, governance practices, and enterprise data models across NRCS systems
- Decompose monolithic database structures into modular, domain-aligned schemas
- Architect service-layer data access patterns to replace direct cross-database queries and embedded stored-procedure business logic
- Design and maintain data models for NASIS, Soil Data Warehouse, Soil Data Marts, and related spatial/tabular datasets
- Align systems with USDA’s cloud-native Lakehouse Data Strategy and Databricks data integration standards
- Register and maintain schemas, interfaces, and metadata in AWS DataZone or Government-directed metadata tooling
- Design, build, and maintain AWS-native data engineering pipelines for batch, streaming, geospatial, and near-real-time workloads
- Modernize SSIS ETL/ELT pipelines using AWS Glue, Databricks, and PySpark
- Build and operate AWS DMS full-load and CDC pipelines for SQL Server-to-PostgreSQL/PostGIS migration
- Implement Delta Lake standards, partitioning strategies, and performance tuning
- Develop serverless orchestration workflows with Lambda, EventBridge, and Step Functions
- Implement data quality controls, validation, reconciliation, monitoring, and audit-ready evidence
- Provide senior-level DBA support for SQL Server, PostgreSQL/PostGIS, Aurora, and DynamoDB environments
- Lead database schema versioning, change tracking, and deployment automation using Liquibase and approved CI/CD processes
- Execute database re-platforming, dependency decoupling, and modernization activities
- Develop application-specific recovery runbooks aligned with DR/COOP requirements
- Design and implement AI/ML and Generative AI solutions using Bedrock, SageMaker, and OpenSearch
- Apply LangChain, embeddings, and RAG patterns to documentation, schema analysis, and DevOps workflows
- Support AI-assisted detection of redundant data flows, schema drift, and integration simplification opportunities
- Leverage authorized AI-enabled platforms for legacy system discovery, business logic extraction, and modernization
- Support urgent AWS migration from DISC data centers, including troubleshooting, testing, and operational adjustments
- Support on-premises-to-AWS database and infrastructure migration, provisioning, re-architecture, validation, and issue resolution
- Design and execute data migration, transformation, test data management, and privacy-preserving activities
- Maintain audit-ready documentation for architecture decisions, schema changes, pipeline configurations, and modernization artifacts
- Enforce FPAC architectural principles, secure coding standards, and NIST SP 800–53 controls
- Conduct architecture reviews, design assurance gates, and code reviews
- Deliver knowledge-transfer sessions to Government personnel and incoming vendors
- Maintain troubleshooting playbooks, runbooks, and knowledge articles
Requirements:
- 7 years of progressive experience in data architecture, data engineering, and database administration across enterprise environments
- 5+ years of hands-on experience designing and deploying data solutions on AWS
- Direct experience with S3, Glue, EMR/Spark, Lambda, Step Functions, DMS, RDS (PostgreSQL, Aurora), DynamoDB, OpenSearch, and Lake Formation
- Deep expertise in Microsoft SQL Server and PostgreSQL/PostGIS
- Experience with database decoupling and monolithic database decomposition
- Proven experience building production data pipelines for batch, streaming, and geospatial workloads
- Experience modernizing legacy ETL (SSIS) to cloud-native frameworks
- Strong proficiency in SQL/T-SQL, Python, and PySpark
- Working knowledge of Bash/PowerShell for automation
- Ability to design and implement enterprise data architectures including data warehouses, data lakes, lakehouses (Delta Lake), and service-layer integration patterns
- 3+ years of experience supporting federal IT programs
- Familiarity with FISMA, NIST RMF, ATO processes, and federal change management requirements
- Experience with CI/CD pipelines, Git-based version control, Terraform or CloudFormation, Liquibase, and automated quality/security gates
- Experience working within SAFe Agile or equivalent iterative delivery frameworks, including backlog management in Jira
- Preferred: Direct experience with USDA systems
- Preferred: Experience with FPAC IT governance, the Technical Guidance Framework (TGF), and FPAC CI/CD pipeline standards
- Preferred: Hands-on experience with AWS Bedrock, SageMaker, and Generative AI patterns (RAG, embeddings, natural-language-to-SQL, LangChain)
- Preferred: Experience with geospatial data engineering, including PostGIS, GeoPackage, ArcGIS WFS/WMS services, and spatial data pipelines
- Preferred: Experience with AI-enabled legacy modernization platforms (e.g., Rhino.ai or equivalent)
- Preferred: Azure experience including Synapse, ADF, ADLS, Azure ML Studio, and Databricks on Azure
- Preferred: Relevant certifications such as AWS Solutions Architect, AWS Data Analytics Specialty, Azure Data Engineer Associate (DP–203), or equivalent
- Preferred: Master’s degree in Computer Science, Data Science, or related field
- USDA Public Trust security clearance requirement
Benefits:
- Paid vacation
- Medical insurance
- Dental insurance
- Vision insurance
- Matching 401K plan
- Tuition/training reimbursement
- Long-Term Disability
- Short-Term Disability
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