AI/ML Data Engineer- Hybrid (US Citizens/ Green Cards- Local to DMV only)

Swingtech; Washington (District of Columbia); Hybrid; USD 110,000 - 165,000; Full time

Benefits offered by this job

PTO 15 days

Holidays 11

Medical Insurance

Dental Insurance

Vision Insurance

Disability Insurance

Life Insurance

401k

Training Budget

Referral Bonus

Job summary

Swingtech in Washington, DC is hiring an AI/ML Data Engineer for a hybrid role. You will design data pipelines, ingest diverse sources, and enable AI/ML workflows with data governance.

Strong SQL/Python and cloud experience are required, and on-site work is 3 days a week at the DC area client site. Responsibilities include building ETL/ELT pipelines, implementing document ingestion with OCR and embeddings, and ensuring data quality and security across training and production datasets.

Qualifications

• Bachelor’s degree in a related technical field.
• At least four years of data engineering/ETL experience.
• Strong SQL and Python development skills.
• Experience designing data pipelines and integrating APIs, databases, or data lakes.
• Familiarity with cloud data services and data governance.

Responsibilities

• Design, build, test, deploy, and maintain scalable data pipelines for batch, streaming, near-real-time, and event-driven workloads.
• Integrate approved agency data sources, APIs, file stores, document repositories, relational databases, data lakes, data warehouses, and external sources.
• Develop ETL/ELT pipelines for extraction, validation, transformation, and loading.
• Implement document-ingestion pipelines with OCR, metadata extraction, PII handling, and embeddings.
• Create and maintain data models, metadata, lineage, and data-quality controls.
• Implement data security measures including access controls and encryption.
• Collaborate with AI/ML engineers to optimize retrieval quality and vector stores.

Skills

SQL

Python

Data pipelines

Education

Bachelor's degree

Tools

AWS

Azure

GCP

Job description

AI/ML Data Engineer- Hybrid (US Citizens/ Green Cards- Local to DMV only)

Swingtech Washington, District of Columbia, United States

About this position

About Swingtech

Swingtech delivers innovative Information Technology and Professional Support services to a diverse range of clients across the federal and intelligence communities. With over 15 years of trusted experience as a systems integrator, we apply agile methodologies and deep industry insight to help our customers achieve greater efficiency, compliance, and cost savings. At Swingtech, we’re committed to excellence and long-term success for our clients and our team.

Position Summary

The AI/ML Data Engineer develops and sustains the secure data pipelines, data products, retrieval foundations, and governance controls that enable DOL’s AI/ML solutions. The position supports structured, semi-structured, and unstructured data sources used for analytics, AI/ML development, document intelligence, RAG, and production AI applications.

• Design, build, test, deploy, and maintain scalable data pipelines for batch, streaming, near-real-time, and event-driven workloads.
• Integrate approved agency data sources, APIs, file stores, document repositories, relational databases, data lakes, data warehouses, and authorized external sources.
• Develop ETL/ELT pipelines for data extraction, validation, transformation, normalization, enrichment, de-identification, metadata management, and loading.
• Implement document-ingestion pipelines that support OCR, parsing, classification, metadata extraction, PII detection/redaction, chunking, embeddings, vector indexing, and retrieval workflows.
• Create and maintain data models, schemas, data dictionaries, metadata structures, catalog records, and data-quality controls.
• Implement data lineage, source provenance, dataset versioning, retention, access controls, and auditability for training, validation, evaluation, and production datasets.
• Preserve the separation of training, validation, and final evaluation datasets through controlled access, versioning, and documented lifecycle processes.
• Develop and monitor data-quality measures, including completeness, accuracy, timeliness, duplication, validity, freshness, distribution drift, and labeling quality.
• Apply data minimization, masking, encryption, access controls, de-identification, and least-privilege safeguards to PII, CUI, and other protected DOL data.
• Collaborate with AI/ML Engineers to optimize retrieval quality, embeddings, vector stores, hybrid search, reranking, citation traceability, and knowledge-base refresh processes.
• Develop data-pipeline runbooks, technical documentation, source inventories, lineage artifacts, data-quality reports, and operational support procedures.
• Support security, privacy, ATO, Responsible AI, incident response, MLOps, monitoring, and release-readiness activities.

Required Qualifications

• Bachelor’s degree in computer science, data engineering, data science, information systems, software engineering, mathematics, or a related technical discipline.
• At least four years of experience in data engineering, database development, analytics engineering, ETL/ELT development, data-platform implementation, or related work.
• Strong SQL and Python development skills.
• Experience designing data pipelines and integrating APIs, databases, file systems, cloud storage, data warehouses, or data lakes.
• Experience with data modeling, metadata, data quality, data lineage, data transformation, monitoring, and operational support.
• Familiarity with AWS, Azure, Google Cloud, or equivalent cloud data services.
• Knowledge of secure data-handling practices, including access control, encryption, data masking, PII protection, and logging.
• Must be willing to work 3 days onsite at customer site in Washington, DC.

Preferred Qualifications

• Experience with AWS Glue, S3, Athena, Redshift, Lake Formation, Azure Data Factory, Azure Data Lake Storage, Databricks, Snowflake, BigQuery, or equivalent platforms.
• Experience with vector databases or vector-search capabilities, including OpenSearch, pgvector, Pinecone, Weaviate, Milvus, Chroma, FAISS, or similar tools.
• Experience with RAG, document intelligence, OCR, enterprise search, knowledge management, document classification, or content-ingestion pipelines.
• Familiarity with Federal data governance, FedRAMP, FISMA, NIST 800-53, NIST 800-171, CUI, Privacy Act, and records-management requirements.

Summary of Benefits

• 15 PTO days
• 11 paid holidays
• Medical Insurance with – 3 options (HSA with $600 Employer Contribution).
• Dental Insurance with no age limit orthodonture.
• Vision Insurance through EyeMed in and out of network coverage.
• Short Term and Long-Term Disability coverage with 100% premium support,
• Life insurance and AD&D with 100% premium support
• Supplemental Life Insurance
• Critical Care and Accident Insurance availability
• Pet Insurance through Nationwide
• Employee Assistance Program
• 401k with enrollment from day one. 4% deferral by company.
• $1500 Annual Training Budget
• $1500 Referral bonus
• Eligibility for annual merit and discretionary bonus

Equal Opportunity Employer Minority/Female/Veterans/Disabled