Data Engineer: Scalable ETL Pipelines & Data Quality

Maximus; Tampa (FL); On-site; USD 166,000 - 217,000; Full time

Benefits offered by this job

Health insurance

Retirement savings plan

Paid holidays

Paid time off

Job summary

Maximus, Inc. is seeking a Data Engineer in Tampa, FL to build and sustain the enterprise data foundation for POTFF analytics.

You will design scalable pipelines, integrate multiple data sources including the HPDMS system, and ensure data quality, lineage, and governance for secure, reproducible analyses. The role supports data scientists and the enterprise data science team, with DoW IL5 and privacy requirements shaping data handling, access controls, and collaboration across government and

Qualifications

• Bachelor’s degree in a quantitative or computing discipline, or equivalent experience.
• Proficiency in SQL and Python for data engineering.
• Experience building and operating data pipelines with ETL/ELT design and version control (Git).
• Ability to communicate clearly with analysts and non-technical stakeholders.
• Desired: Palantir Foundry, Databricks, Spark, Power BI experience.

Responsibilities

• Design, implement, and maintain scalable ETL/ELT pipelines on the Government-furnished tech stack.
• Fuse disparate data sources into curated, analysis-ready datasets.
• Enforce data quality, lineage, and governance; monitor workloads and resolve failures.
• Develop data models, metadata, and transformation logic under version control; document data sources and steps.
• Prepare data for NLP/LLM use cases and support deployment of analytic products.

Skills

SQL

Python

Data pipelines

ETL/ELT design

Git

Communication

Databricks

Spark

Education

Bachelor’s degree in a quantitative or computing discipline

Tools

Palantir Foundry

Databricks

Apache Spark

Power BI

Job description

Maximus, Inc. is seeking a Data Engineer in Tampa, FL to build and sustain the enterprise data foundation for POTFF analytics.

You will design scalable pipelines, integrate multiple data sources including the HPDMS system, and ensure data quality, lineage, and governance for secure, reproducible analyses. The role supports data scientists and the enterprise data science team, with DoW IL5 and privacy requirements shaping data handling, access controls, and collaboration across government and