Data Engineer, Hybrid (DC Area) – Secure Analytics Pipelines

MANTECH; Arlington (VA); Hybrid; USD 110,000 - 160,000; Full time

Job summary

MANTECH in Arlington, VA seeks a Data Engineer to support IRS mission-critical analytics by designing secure, scalable data pipelines. This hybrid role requires collaboration with data scientists, program managers, and stakeholders to translate requirements into production-ready data solutions.

Responsibilities include building end-to-end pipelines, integrating diverse data types, and delivering well-documented code with a focus on reliability, security, and continuous improvement in agile

Qualifications

• BS degree in statistics, CS, economics, math, analytics, data science, data engineering, or related field.
• 2–7+ years of data science/analytics experience with programming (Python preferred).
• Build and deploy automated data pipelines using Python and SQL.
• Experience with Databricks, AWS, and ML workflow integration.

Responsibilities

• Troubleshoot and resolve data and system issues in cross-functional environments.
• Engineer pipelines for transactional, financial, and textual data for analytics.
• Collaborate with data scientists to deploy Analytics applications and dashboards.
• Develop reusable, well-documented code in Python, SQL, Java, and more.
• Build end-to-end data pipelines for on-prem and cloud environments.
• Produce technical docs and briefings for technical and non-technical audiences.
• Act as technical consultant translating needs into data solutions.

Skills

Python

SQL

Data pipelines

Data engineering

Databricks

AWS

Git

Education

B.S. in CS/Statistics/Data Science

Tools

Databricks

Unity Catalog

PySpark

Spark SQL

Power BI

Tableau

Docker

Job description

MANTECH in Arlington, VA seeks a Data Engineer to support IRS mission-critical analytics by designing secure, scalable data pipelines. This hybrid role requires collaboration with data scientists, program managers, and stakeholders to translate requirements into production-ready data solutions.

Responsibilities include building end-to-end pipelines, integrating diverse data types, and delivering well-documented code with a focus on reliability, security, and continuous improvement in agile