Job Title: Data Architect / Data Engineering Lead
Location: Remote - Temporary 3-4 Month Assignment
Contract: USDA OMNI - NRCS Operations & Maintenance
Security Clearance: USDA Public Trust
Salary Range: $120,000.00 - $135,000.00 per year.
The Data Architect / Data Engineering Lead provides technical leadership for data architecture, data engineering, database modernization, and AI/ML enablement across the NRCS IT ecosystem. This role is responsible for guiding the transformation of legacy data platforms - including monolithic SQL Server environments, SSIS-based ETL pipelines, and tightly coupled cross-database dependencies - into scalable, cloud-native architectures on AWS. The position works in close coordination with the Enterprise Lead Architect, Government Program Managers, and cross-functional delivery teams to execute data management, modernization, and operational sustainment activities under the OMNI contract.
Required Qualifications:- Experience: 7 years of progressive experience in data architecture, data engineering, and database administration across enterprise environments.
- Cloud Platforms: 5+ years of hands-on experience designing and deploying data solutions on AWS, including direct experience with S3, Glue, EMR/Spark, Lambda, Step Functions, DMS, RDS (PostgreSQL, Aurora), DynamoDB, OpenSearch, and Lake Formation.
- Database Technologies: Deep expertise in Microsoft SQL Server and PostgreSQL/PostGIS. Experience with database decoupling and monolithic database decomposition.
- Data Engineering: Proven experience building production data pipelines for batch, streaming, and geospatial workloads. Experience modernizing legacy ETL (SSIS) to cloud-native frameworks.
- Programming: Strong proficiency in SQL/T-SQL, Python, and PySpark. Working knowledge of Bash/PowerShell for automation.
- Architecture: Demonstrated ability to design and implement enterprise data architectures including data warehouses, data lakes, lakehouses (Delta Lake), and service-layer integration patterns.
- Federal IT: 3+ years of experience supporting federal IT programs, with familiarity with FISMA, NIST RMF, ATO processes, and federal change management requirements.
- DevSecOps: Experience with CI/CD pipelines, Git-based version control, Terraform or CloudFormation, Liquibase, and automated quality/security gates.
- Agile/SAFe: Experience working within SAFe Agile or equivalent iterative delivery frameworks, including backlog management in Jira.
Preferred Qualifications:- Direct experience with USDA systems
- Experience with FPAC IT governance, the Technical Guidance Framework (TGF), and FPAC CI/CD pipeline standards.
- Hands-on experience with AWS Bedrock, SageMaker, and Generative AI patterns (RAG, embeddings, natural-language-to-SQL, LangChain).
- Experience with geospatial data engineering, including PostGIS, GeoPackage, ArcGIS WFS/WMS services, and spatial data pipelines.
- Experience with AI-enabled legacy modernization platforms (e.g., Rhino.ai or equivalent).
- Azure experience (Synapse, ADF, ADLS, Azure ML Studio, Databricks on Azure) as a complement to primary AWS focus.
- Relevant certifications: AWS Solutions Architect, AWS Data Analytics Specialty, Azure Data Engineer Associate (DP-203), or equivalent.
- Master's degree in Computer Science, Data Science, or related filed.
Responsibilities:- Data Architecture and Strategy
- Define and maintain data architecture standards, patterns, and governance practices across all NRCS systems, ensuring alignment with FPAC's Technical Guidance Framework (TGF), Cloud Memo directives, and Zero Trust principles.
- Lead conceptual and logical decomposition of monolithic database structures (e.g., NPAD) into domain-aligned, modular schemas that support incremental modernization and cloud migration.
- Architect service-layer data access patterns to replace direct cross-database queries and business logic embedded in stored procedures, reducing architectural fragility and enabling decoupled deployments.
- Design and maintain data models for enterprise soil data systems including NASIS, Soil Data Warehouse (SDW), Soil Data Marts (SDM), and related spatial/tabular datasets.
- Align supported systems with USDA's cloud-native Lakehouse Data Strategy, including adoption of Databricks as the departmental standard data integration tool and elimination of duplicated data copies.
- Register and maintain schemas, interfaces, and metadata in AWS DataZone (or Government-directed metadata tooling), ensuring synchronization across environments.
- Data Engineering and Pipeline Development
- Design, build, and maintain end-to-end data engineering pipelines using AWS-native services (Glue, EMR/Spark, Lambda, Step Functions, EventBridge, DMS, S3, RDS/Aurora PostgreSQL) for batch, streaming, geospatial, and near-real-time workloads.
- Modernize legacy SSIS-based ETL/ELT pipelines to cloud-native equivalents (AWS Glue, Databricks, PySpark), improving scalability, maintainability, and operational efficiency.
- Build and operate AWS DMS full-load and CDC pipelines to support migration of SQL Server databases to PostgreSQL/PostGIS and other target platforms.
- Implement Delta Lake standards, partitioning strategies, and performance tuning across ingestion frameworks for structured, unstructured, and geospatial data.
- Develop serverless orchestration workflows using Lambda, EventBridge, and Step Functions for event-driven processing and automated data operations.
- Implement data quality controls (validation, reconciliation, monitoring) and maintain audit-ready evidence of data management activities.
- Database Operations and Modernization
- Provide senior-level DBA support for SQL Server clusters (including high-availability configurations, failover groups, and large-scale datasets exceeding 50 TB), as well as PostgreSQL/PostGIS, Aurora, and DynamoDB environments.
- Lead database schema versioning, change tracking, and deployment automation using Liquibase and Government-approved CI/CD processes.
- Execute database modernization activities including re-platforming from on-premises SQL Server to AWS RDS/Aurora, decoupling monolithic database dependencies, and eliminating cross-database stored procedure calls.
- Develop and maintain application-specific database recovery runbooks, including validated restore procedures, dependency mapping, and configuration baselines aligned with DR/COOP requirements.
- AI/ML and Generative AI Enablement
- Design and implement AI/ML and Generative AI solutions using AWS services (Bedrock, SageMaker, OpenSearch) to support natural-language-to-SQL, automated metadata generation, conversational technical assistance, and AI-powered data pipeline optimization.
- Apply GenAI tooling (e.g., Bedrock, LangChain, embeddings, RAG patterns) to accelerate documentation, schema analysis, and DevOps workflows.
- Support AI-assisted analysis to detect redundant data flows, schema drift, and opportunities to simplify data integrations.
- Leverage AI-enabled platforms (e.g., Rhino.ai or equivalent) for legacy system discovery, business logic extraction, and modernization acceleration where authorized by the Government.
- AWS Migration Support
- Provide data engineering and DBA expertise in support of the urgent AWS migration from DISC data centers, including troubleshooting, testing, and implementing operational adjustments to maintain continuity of mission-critical business functions (e.g., payment processing).
- Support full on-premises to AWS migration for databases and data infrastructure, including provisioning, lift-and-shift, re-architecture, data migration validation, and issue resolution.
- Design and execute data migration and transformation activities, including test data management and privacy-preserving techniques for non-production environments.
- Governance, Compliance, and Knowledge Transfer
- Maintain audit-ready documentation for all data architecture decisions, schema changes, pipeline configurations, and modernization artifacts in Government-designated systems of record.
- Enforce FPAC architectural principles, secure coding standards, and NIST SP 800-53 controls across all data engineering and database activities.
- Conduct architecture reviews, design assurance gates, and code reviews for data-related deliverables, ensuring adherence to quality standards and FPAC SonarQube thresholds.
- Deliver knowledge transfer sessions to Government personnel and incoming vendors during transition periods, including complete documentation handoff of data systems, pipelines, and architectural decisions.
- Maintain and update troubleshooting playbooks, runbooks, and knowledge articles for data systems in Government-designated repositories.
Benefits:Competitive compensation and benefits packages including paid vacation, medical, dental, vision, matching 401K plan, tuition/training reimbursement, and Long & Short-Term Disability.
Physical Demands:Sitting and working on a computer for long, continuous periods each day; effective communications by telephone, email, and face-to-face; standing, walking, and sitting; handling and feeling objects or controls; reaching; talking and hearing; lifting and/or moving up to 10 pounds; and specific vision abilities including close vision, distance vision, color vision, peripheral vision, depth perception, and the ability to adjust and focus.
Work Environment: The noise level in the work environment is usually moderate.
