AI/ML Data Engineer- Hybrid (s/ s- Local to DMV only)

Washington, DC, US • Posted 2 days ago • Updated 4 hours ago

Full Time

On-site

Compensation information provided in the description

Fitment

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Job Details

Skills

DMV
Information Technology
Agile
Regulatory Compliance
Cost Reduction
Unstructured Data
Streaming
Real-time
Relational Databases
Data Extraction
Normalization
Extraction
Workflow
Evaluation
Distribution
Collaboration
Machine Learning (ML)
Knowledge Base
Technical Writing
Artificial Intelligence
Incident Management
Machine Learning Operations (ML Ops)
Computer Science
Data Science
Information Systems
Software Engineering
Mathematics
Data Engineering
Analytics
Extract
Transform
Load
ELT
SQL
Python
Database
File Systems
Cloud Storage
Data Warehouse
Data Modeling
Meta-data Management
Data Quality
Google Cloud
Google Cloud Platform
Cloud Computing
Access Control
Encryption
Data Masking
Amazon Web Services
Amazon S3
Amazon Redshift
Microsoft Azure
Data Lake
Storage
Databricks
Snow Flake Schema
Vector Databases
Optical Character Recognition
Enterprise Search
Knowledge Management
Data Governance
FedRAMP
FISMA
NIST 800-53
NIST SP 800 Series
Privacy
Records Management
Health Insurance
Network
Life Insurance
Insurance
Training
Budget

DMV
Information Technology
Agile
Regulatory Compliance
Cost Reduction
Unstructured Data
Streaming
Real-time
Relational Databases
Data Extraction
Normalization
Extraction
Workflow
Evaluation
Distribution
Collaboration
Machine Learning (ML)
Knowledge Base
Technical Writing
Artificial Intelligence
Incident Management
Machine Learning Operations (ML Ops)
Computer Science
Data Science
Information Systems
Software Engineering
Mathematics
Data Engineering
Analytics
Extract
Transform
Load
ELT
SQL
Python
Database
File Systems
Cloud Storage
Data Warehouse
Data Modeling
Meta-data Management
Data Quality
Google Cloud
Google Cloud Platform
Cloud Computing
Access Control
Encryption
Data Masking
Amazon Web Services
Amazon S3
Amazon Redshift
Microsoft Azure
Data Lake
Storage
Databricks
Snow Flake Schema
Vector Databases
Optical Character Recognition
Enterprise Search
Knowledge Management
Data Governance
FedRAMP
FISMA
NIST 800-53
NIST SP 800 Series
Privacy
Records Management
Health Insurance
Network
Life Insurance
Insurance
Training
Budget

Summary

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.

Essential Duties

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
Flexible work arrangements

Equal Opportunity Employer Minority/Female/Veterans/Disabled

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 90882430
Position Id: e74b7234b23c59221d04976a8fcc4646
Posted 2 days ago

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