Data & Analytics Architect

Accenture Federal Services•Washington, DC

2d•$116,900 - $243,100

About The Position

At Accenture Federal Services, our purpose is to make the US federal government stronger and safer, and to improve the lives of citizens through technology and ingenuity. We are a technology company within the global Accenture network, comprising over 13,000 employees dedicated to serving clients across defense, national security, public safety, civilian, and military health organizations. Recognized as a Glassdoor Top 100 Best Place to Work, we foster a collaborative and supportive community where employees are empowered to grow, learn, and thrive through hands-on experience, certifications, and industry training. Join us to drive meaningful, lasting change that advances missions and propels the government forward.

Requirements

Bachelor’s degree required; advanced degree in a related field preferred.
Experience designing and deploying cloud‑based data architectures (Azure, Databricks, AWS, SQL).
Proficiency with modern data engineering tools and languages (Databricks, Python, R, SQL, Git, CI/CD tooling).
Experience building large‑scale ingestion pipelines, automated reporting feeds, and cloud‑native processing workflows.
Strong ability to translate program needs into scalable, maintainable technical designs.
Excellent communication, documentation, and stakeholder engagement skills.

Nice To Haves

Experience working in federal, public health, or similarly complex organizational environments.

Responsibilities

Develop and maintain end‑to‑end architectures for data streams, ingestion pipelines, and cloud‑based processing environments.
Define technical standards, patterns, and reusable components that support efficient data collection, integration, and operational performance.
Provide architectural guidance for modernization efforts, including transitioning legacy workflows into Databricks‑native and cloud‑optimized designs.
Design, build, and optimize ETL/ELT pipelines for data acquisition, transformation, validation, and structured delivery.
Lead technical prototyping and rapid development of new ingestion and processing capabilities.
Implement quality assurance frameworks such as automated testing, CI/CD, version control workflows, and operational monitoring for reliability and reproducibility.
Oversee and improve operational processes for high‑volume, multi‑source data streams.
Provide engineering support for financial data workflows and other specialized data streams.
Contribute technical expertise to modernize dashboards or analytic systems by improving upstream data pipelines and data structures.
Collaborate on next‑generation Databricks capabilities that enhance data processing, orchestration, and automation.
Participate in platform design discussions to ensure future architectures are scalable and support emerging use cases.
Partner with cross‑functional teams to strengthen data literacy through documentation and knowledge sharing.
Deliver training on pipeline best practices, workflow optimization, and modern engineering patterns.
Mentor junior team members and support a community of practice centered on data engineering and cloud‑native architecture.