Big Data Engineer / Developer
Accenture Federal ServicesWashington, DCPosted 21 March 2026
Job Description
At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. 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 within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer 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!
Job Overview: As a GCP Data Pipeline Developer BigQuery Data Engineer, you will be responsible for designing, developing, and maintaining data pipelines on Google Cloud Platform (GCP). Your role will involve working with BigQuery to analyze and optimize large datasets, as well as implementing ETL processes to ensure data quality and integrity. Proficiency in foundational GCP services, BigQuery, data engineering principles, SQL, and PySpark will be essential for success in this position. Additionally, experience with ETL tools such as Qlik Data Integration or FiveTran would be a valuable asset in this role.
In this role, you will have the opportunity to work on complex data projects that require a deep understanding of cloud-based data processing and analysis. Your expertise in GCP and BigQuery will be crucial in developing efficient data pipelines that meet the organization's data processing needs. Strong SQL skills will be necessary for querying and manipulating data within BigQuery, while experience with PySpark will enable you to perform advanced data transformations and analytics. Overall, your ability to leverage these tools and technologies effectively will be key to driving data-driven decision-making within the organization.
Key Responsibilities:
Develop and maintain GCP data pipelines.
Design and optimize BigQuery data structures.
Utilize SQL and PySpark for data processing.
Collaborate with team members on data engineering projects.
Implement ETL processes using tools like GCP Dataflow, Qlik Data Integration, or FiveTran.
Here's What You Need:
Proficiency in foundational GCP services.
Strong experience with BigQuery.
Solid understanding of data engineering principles.
Advanced SQL skills for querying and manipulating data.
Experience with PySpark for data transformations and analytics.
Familiarity with ETL tools such as Qlik Data Integration or FiveTran.
Ability to design and implement scalable data solutions.
Strong analytical and problem-solving skills.
Excellent collaboration and communication skills.
US Citizenship required, No Dual Citizenship
Bonus points if you have:
Experience with other cloud platforms and big data technologies.
Previous experience in a similar role within a data-driven organization.
Certifications related to GCP, BigQuery, or data engineering.
As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of
California, Colorado, Hawaii, Illinois, Maryland,
Massachusetts,
Minnesota, New Jersey, New York, Washington, Vermont, the District of Columbia, and the city of Cleveland
. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits.
You can find more information on benefits here.
We accept applications on an on-going basis and there is no fixed deadline to apply.
The pay range for the states of California, Colorado, Hawaii, Illinois, Marylan ... (truncated, view full listing at source)
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