Data Engineer Associate Manager

Accenture•Arlington, VA

35d

About The Position

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people.â¯Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company and part of global Accenture, to do work that matters in a collaborative and caring community, where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! As a senior Data Engineer, you will be a key technical contributor on the team building and maintaining the critical data pipelines for a data platform. You will apply your deep expertise to design, develop, and optimize robust ETL/ELT processes that move and transform data for DoD-wide use. In this role, you will not only build solutions but also mentor junior engineers and help drive the adoption of modern data engineering practices and automation.

Requirements

6+ years of experience in data engineering
Strong experience with the development and maintenance of extract, transform, and load (ETL) tools and services
Proficiency in Python, SQL, Spark, and PySpark
Hands-on experience with cloud environments (AWS, Azure) and data platforms like Databricks, Palantir, or Snowflake
Experience working in an Agile/Scrum development environment
Familiarity with data orchestration and data quality processes
Active TS Clearance or TS/SCI Clearance

Nice To Haves

Experience working in high-security DoD environments (e.g., SIPR, JWICS)
Hands-on experience with Databricks Delta Live Tables and Terraform
Experience with containerization technologies like Docker or Kubernetes
Knowledge of COTS and open-source data engineering tools such as NiFi or ElasticSearch

Responsibilities

Design, build, and maintain scalable and resilient data pipelines for both new data sources and existing systems within the data platform ecosystem.
Implement and optimize pipelines using modular patterns, such as Databricks Delta Live Tables, following governance from the architecture team.
Develop and integrate automated monitoring, alerting, and data quality checks into every pipeline to reduce downtime and ensure data integrity.
Utilize Infrastructure-as-Code (IaC) with tools like Terraform to create consistent, repeatable deployments and CI/CD processes.
Analyze complex source data formats and collaborate with data scientists and stakeholders to design transformations that meet mission objectives.
Participate in and lead code reviews, enforce best practices, and mentor junior data engineers.
Troubleshoot and resolve complex issues with data pipelines, and contribute to the ongoing improvement of O&M processes.

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