Hybrid AI/ML Data Engineer — Scalable Data Pipelines

DataJobs; Washington (District of Columbia); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

PTO 15 days

11 paid holidays

Medical Insurance - 3 options

Job summary

DataJobs in Washington, DC is seeking an AI/ML Data Engineer to build and sustain secure data pipelines, data products, and governance controls for DOL AI/ML solutions. This hybrid role supports structured, semi-structured, and unstructured data across analytics, document intelligence, RAG, and production AI applications.

Responsibilities include designing scalable pipelines, integrating diverse data sources, implementing ETL/ELT, and enforcing data lineage, quality, and security.

Qualifications

• Bachelor’s degree in a technical field.
• At least four years of data engineering or analytics engineering experience.
• Strong SQL and Python development skills.
• Experience designing data pipelines and integrating diverse data sources.
• Experience with data modeling, metadata, data quality, and data lineage.
• Familiarity with AWS, Azure, Google Cloud, or equivalent cloud data services.
• Knowledge of secure data handling, access controls, encryption, and PII protection.
• Willingness to work 3 days onsite at a customer site in Washington, DC.

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 including APIs, file stores, databases, data lakes, and data warehouses.
• Develop ETL/ELT pipelines for extraction, validation, transformation, enrichment, and loading.
• Implement document-ingestion pipelines with OCR, parsing, metadata extraction, and retrieval workflows.
• Create and maintain data models, schemas, metadata structures, and data-quality controls.
• Implement data lineage, provenance, dataset versioning, retention, and access controls.
• Preserve separation of training/validation/evaluation datasets with controlled access and lifecycle processes.
• Develop data-quality measures for completeness, accuracy, timeliness, and labeling quality.
• Apply data minimization, masking, encryption, and least-privilege safeguards for protected data.
• Collaborate with AI/ML engineers to optimize retrieval quality, embeddings, and vector stores.
• Develop data-pipeline runbooks and technical documentation; support security, privacy, and MLOps.
• Assist with monitoring, incident response, and release-readiness activities.

Skills

SQL

Python

Data pipelines

Data modeling

Metadata & lineage

Education

Bachelor's degree

Tools

AWS

Azure

Google Cloud

AWS Glue

S3

Athena

Redshift

Lake Formation

Databricks

Snowflake

BigQuery

OpenSearch

FAISS

RAG

Job description

DataJobs in Washington, DC is seeking an AI/ML Data Engineer to build and sustain secure data pipelines, data products, and governance controls for DOL AI/ML solutions. This hybrid role supports structured, semi-structured, and unstructured data across analytics, document intelligence, RAG, and production AI applications.

Responsibilities include designing scalable pipelines, integrating diverse data sources, implementing ETL/ELT, and enforcing data lineage, quality, and security.