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# Senior Data Engineer

- **Company:** TEKSYSTEMS INC.
- **Location:** Farmington, MI, United States
- **Experience:** Expert
- **Salary:** $156,000 - $170,560
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon S3, Databases, Data Architecture, Extract Transform Load (ETL), Data Security, Amazon DynamoDB, Python (Programming Language), PostgreSQL, Metadata, Software Engineering, SQL Databases, Unstructured Data, Data Processing, Data Ingestion, Amazon Relational Database Service, Pgvector, Data Pipelines
- **Published:** November 7, 2026
- **Apply:** https://www.thejobnetwork.com/job/5214920b-f792-49b4-b034-4525181f6cca/senior-data-engineer

## About the Role

Data architecture, Data, Strong ability to collaborate across AI, Software Engineering Testing, Architecture and Security teams, Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors.

## Description

The Senior Data Engineer is responsible for designing, building, and supporting scalable and secure data solutions for enterprise Wealth & Asset Management applications. The role focuses on data ingestion, transformation, storage, integration, quality, governance, and processing across structured and unstructured data sources., Design and develop scalable data ingestion and ETL/ELT pipelines.

Build solutions for structured, semi-structured, and unstructured data.

Develop reusable data-processing and transformation components using Python and SQL.

Design and support data models using PostgreSQL, Amazon RDS, DynamoDB, and Amazon S3.

Support document ingestion and extraction using Amazon Textract, where applicable.

Prepare and transform data for application, search, analytics, and AI-enabled use cases.

Support vector-based retrieval using PostgreSQL/pgvector, where required.

Implement data quality, validation, reconciliation, metadata, lineage, retention, and governance controls.

Implement secure data access and encryption for sensitive information.

Optimize data pipelines and databases for performance, reliability, scalability, and cost.

Implement monitoring and troubleshoot data-processing and integration issues.