Data Engineer: Agile Pipelines for BI Analytics

Cgsfederal; Dallas (TX); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Health, Dental, and Vision

Life Insurance

401(k)

FSA (Health, Dependent Care, and Comms

PTO & Holidays

Job summary

CGS, based in the Dallas area, is seeking a Data Engineer to advance a federal Data Analytics and BI platform. You will join a cross‑functional Agile team to design and implement scalable data pipelines, storage, and provisioning for data consumers.

The role emphasizes API‑first design, CI/CD, and lean‑agile engineering practices, and requires collaboration with program management, engineers, and UX researchers to turn diverse data sources into actionable insights while maintaining security and

Qualifications

• Must be a US citizen and able to obtain a Public Trust clearance.
• 7+ years of IT experience designing and managing large, complex data sets and models.
• Experience building data pipelines from diverse sources (structured and unstructured).
• Proficiency in ETL development and data validation; strong SQL, Python, and SAS skills.

Responsibilities

• Develop data pipelines end-to-end to store, manage, and provision data to consumers.
• Contribute as an Agile/Scrum team member; follow lean-agile engineering practices.
• Write code to ensure performance and reliability of data extraction and processing.
• Automate data ingestion and support CI/CD pipelines; use version control.
• Collaborate with cross-functional teams including QA, UX researchers, designers, and product managers.

Skills

ETL pipelines

Python

SQL

R

SAS

Big data concepts

CI/CD

Git

API design

Agile/Scrum

Tools

PostgreSQL

Tableau

Power BI

Linux Shell

Git

Job description

CGS, based in the Dallas area, is seeking a Data Engineer to advance a federal Data Analytics and BI platform. You will join a cross‑functional Agile team to design and implement scalable data pipelines, storage, and provisioning for data consumers.

The role emphasizes API‑first design, CI/CD, and lean‑agile engineering practices, and requires collaboration with program management, engineers, and UX researchers to turn diverse data sources into actionable insights while maintaining security and