Data Scientist - Senior

Accenture Federal Services•Chantilly, VA

9d•$94,000 - $178,700

About The Position

The posting title is “Data Scientist - Senior,” although the role description identifies the position as a Senior Data Engineer. The role provides expert leadership in designing, building, and maintaining data systems that support advanced analytics and visual intelligence applications. It develops scalable data pipelines, builds large relational databases, and ensures data flows smoothly and securely across the organization. The role also integrates new data systems with existing platforms and helps convert structured and semi-structured data into actionable insights. The position involves building and maintaining data pipelines for visual analytics and high-performance data processing; designing and optimizing enterprise relational databases; integrating data systems with existing warehouses; and applying open-source, commercial off-the-shelf (COTS), and government off-the-shelf (GOTS) technologies. It also develops database operations, programming, and security practices and collaborates with teams to improve data quality and usability. The role requires US citizenship and an active TS/SCI CIP clearance, along with at least eight years of experience. The posting includes a base pay range of $94,000–$178,700 USD for specified states and the District of Columbia. Accenture Federal Services describes a collaborative workplace and mentions opportunities for hands-on experience, certifications, and industry training. Benefits are referenced through a benefits-information link, but specific benefits are not listed.

Requirements

US citizen with an active TS/SCI CIP clearance.
At least 8 years of experience.
Knowledge of data engineering, database development, or related areas.
Strong experience with relational databases, SQL, and large-scale data design.
Hands-on experience building pipelines for structured and semi-structured data.
Familiarity with analytics, visualization technologies, and high-performance or distributed computing.
Experience integrating new systems with enterprise data warehouses.
Understanding of secure data practices and zero-trust principles.
Strong communication and problem-solving skills.

Nice To Haves

Experience with government or multi-enclave data environments.
Background with data visualization platforms or visual analytics applications.
Experience with cloud data platforms or hybrid architectures.
Degree in Data Engineering, Computer Science, or a related field.
Experience with an in-house custom-developed application featuring an end-user UI and ETL UI.
Kubernetes.
Terraform.
GitLab CI/CD.
JFrog Artifactory.
AWS Cloud Services.
Angular.
.NET C#.
MySQL.
Elasticsearch or OpenSearch.
Integration of reasoning components, retrieval systems, databases, and AI/GenAI services.
ETL.
Python.
RabbitMQ.
Celery.
Redis or Valkey.
Postgres or Microsoft SQL.
Complex data parsing and streamlined ingestion.
Provenance and end-to-end data lineage tracking.
Schema-aligned ingestion and normalization of diverse structured and unstructured data.

Responsibilities

Build and maintain data pipelines supporting visual analytics applications and high-performance data processing.
Transform structured and semi-structured data into usable, actionable information.
Design and construct large enterprise relational databases and ensure efficient performance.
Integrate new data systems with existing data warehouses and refine system performance.
Use open-source, COTS, and GOTS technologies to support analytics and data workflows.
Develop strategies, standards, and best practices for database operations, programming, and security.
Collaborate with teams to analyze data needs and enhance data quality and usability.

Benefits

Hands-on experience, certifications, and industry training are described as opportunities for growth and learning; specific benefits are not enumerated.

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