Data / Backend Engineer

Aretec Inc•,

8d•Remote

About The Position

At Aretec, Inc., we are catalysts for change within the federal government landscape. Specializing in advanced analytics, machine learning, data analysis, cybersecurity, and business optimization, we empower federal agencies to achieve their most critical missions. As a premier partner and prime vendor, we deliver innovative, high-impact solutions that address complex challenges and drive national progress. Our commitment to excellence and innovation positions us at the forefront of transforming governmental operations, enhancing efficiency, and making a lasting difference in the lives of citizens. Aretec 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, normalization, SQL workflows, entity-resolution support, backend integrations, and automated tests across approved data sources.

Requirements

Strong experience building data connectors, ingestion pipelines, or ETL/ELT workflows.
Strong SQL skills and experience working with relational or analytical data stores.
Experience with Python or another language used for data and backend engineering.
Knowledge of metadata harmonization, normalization, schema mapping, and data-quality controls.
Experience integrating backend services and APIs.
Understanding of entity-resolution, deduplication, or record-linkage concepts.
Experience with automated testing, troubleshooting, documentation, and reliable pipeline operation.

Nice To Haves

Experience with enterprise search, document-oriented data, retrieval systems, or AI-ready data pipelines.
Experience working with governed enterprise data platforms and access-controlled sources.
Familiarity with data lineage, observability, reconciliation, and privacy or security controls.
Experience delivering data capabilities in federal, regulated, or security-conscious environments.

Responsibilities

Design and build secure connectors to approved internal and external data sources.
Develop reliable ingestion, ETL, transformation, and data-validation pipelines.
Harmonize and normalize metadata so information from different sources can be searched, joined, traced, and evaluated consistently.
Write and optimize SQL used by backend services, analysis workflows, and reporting features.
Support entity resolution, deduplication, record linkage, and data-quality improvement.
Integrate data services with greenfield AI solution and existing enterprise-search or enterprise-data-platform capabilities.
Help evaluate source onboarding according to analytical value, implementation complexity, cost, access limitations, and AI-readiness.
Create automated unit, integration, regression, reconciliation, and data-quality tests.
Document lineage, transformations, schemas, operational dependencies, and failure-recovery procedures.
Collaborate with AI/backend and full-stack engineers to provide performant, well-structured, traceable data services.