Data Engineer – ETL, SQL & AI Pipelines (Remote)

Aretec, Inc.; United States; On-site; USD 90,000 - 150,000; Full time

Benefits offered by this job

Health, Dental, and Vision Insurance

401(k) Plan with Employer Match

Certification Stipends

Professional Development Opportunities

Flexible Work Arrangements, including远

Job summary

Aretec, Inc. is seeking a Data / Backend Engineer to expand the trusted data foundation for our client's greenfield AI solution. You will build connectors, ingestion and ETL pipelines, metadata harmonization across approved sources.

You will collaborate with AI/backend and full-stack engineers to deliver secure, scalable data services, implement tests, and ensure data quality, lineage, and observability in a mission-driven federal context.

Qualifications

• Experience building data connectors, ingestion pipelines, or ETL/ELT workflows.
• Strong SQL skills with relational/analytic data stores.
• Proficient in Python or similar for data/backend engineering.
• Knowledge of metadata harmonization, normalization, and data quality controls.
• Experience integrating backend services and APIs.
• Understanding of entity-resolution, deduplication concepts.
• Experience with automated testing and reliable pipeline operation.

Responsibilities

• Design secure connectors to data sources.
• Build ingestion, ETL, transformation pipelines.
• Harmonize and normalize metadata for searchability.
• Write and optimize SQL for backend services and analytics.
• Document lineage, schemas, and failure-recovery procedures.
• Collaborate with AI/backend and full-stack engineers.

Skills

Data pipelines

SQL skills

Python

Metadata

Backend APIs

Entity resolution

Automated tests

Job description

Aretec, Inc. is seeking a Data / Backend Engineer to expand the trusted data foundation for our client's greenfield AI solution. You will build connectors, ingestion and ETL pipelines, metadata harmonization across approved sources.

You will collaborate with AI/backend and full-stack engineers to deliver secure, scalable data services, implement tests, and ensure data quality, lineage, and observability in a mission-driven federal context.