Data Scientist; TS​/SCI Poly

At GCI, we solve the hard problems. As a Data Scientist, a typical day will include the following duties:

• Demonstrated experience building production data pipelines and ETL/ELT workflows at scale.
• Demonstrated experience with Apache Spark and PySpark for distributed data processing.
• Demonstrated experience with advanced Python programming skills including data manipulation libraries (Pandas, Num Py) and data engineering best practices.
• Demonstrated experience understanding data security, privacy, governance, and compliance principles.
• Demonstrated experience with workflow orchestration tools such as Step Functions and Airflow.
• Demonstrated experience with containerization such as Docker or Podman, and deploying data applications in cloud environments.
• Demonstrated experience with AWS services (in particular S3, Lambda, and Step Functions).
• Demonstrated experience with Postgre
  
  SQL and MySQL in production environments, including performance tuning and schema design.
• Demonstrated experience with SQL and query optimization for complex analytical workloads.
• Demonstrated experience with version control (Git) and CI/CD practices for data pipelines.
• Demonstrated experience working with stakeholders to understand data requirements, assess feasibility, and design appropriate solutions with minimal oversight.
• Demonstrated experience with strong problem-solving and debugging skills for data quality issues, pipeline failures, and performance bottlenecks.

• Demonstrated experience with data lakehouse architectures using Apache Iceberg.
• Demonstrated experience configuring, deploying, and integrating data platform components:
  Apache Ranger (access control and data governance), Trino (distributed SQL query engine), Data catalogs (Unity Catalog OSS, Apache Polaris, etc.), Apache Superset (data visualization and dashboarding).
• Demonstrated experience with Bash scripting for automation and data processing tasks.
• Demonstrated experience with Infrastructure as Code (Terraform or Cloud Formation) for data infrastructure.
• Demonstrated experience with tracking data lineage and associated tooling such as Open Lineage.
• Demonstrated experience with Java.
• Demonstrated experience with data quality frameworks, testing methodologies, and validation strategies.
• Demonstrated experience or background with large-scale data migrations or platform modernization efforts.
• Demonstrated experience integrating AI/ML services and models (translation, OCR, speech-to-text, NLP, language detection, topic modeling), LLMs, and RAG (retrieval-augmented generation) pipelines.
• Demonstrated experience with geospatial data processing (H3, PostGIS, or similar).
• Demonstrated experience Contributing to data engineering documentation, best practices, or design patterns.
• Demonstrated experience with No
  
  SQL databases (Dynamo
  
  DB, etc.).
• Demonstrated experience with excellent written and verbal communication skills with both technical and non-technical audiences.
• A candidate must be a US Citizen and requires an active/current TS/SCI with Polygraph clearance.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans