Sr. DBA

CGI•Pittsburgh, PA

4d•Onsite

About The Position

We are looking for a passionate and skilled DBA to join our growing data and analytics team. If you enjoy building scalable data pipelines, optimizing large-scale databases, and working with modern big data technologies, this role is for you. This role must be filled 5 days per week in the client office in either Strongsville OH or Pittsburgh PA. For this role on this particular client engagement, employer sponsorship of immigration‑related visa and/or green card status as part of the PERM process will not be available.

Requirements

5+ years of hands-on experience with query optimization, indexing, partitioning, and database performance tuning.
4+ years of strong programming experience in Python and PySpark for large-scale data processing.
4+ years of experience designing and developing scalable ETL/data ingestion pipelines.
Experience with processing, storing, archival, and purging strategies for large-scale datasets.
3+ years of experience working with modern open table formats such as Apache Iceberg and Delta Lake.
3+ years of hands-on experience with Tableau for building interactive dashboards and data visualizations.
Strong understanding of data quality, validation, integrity, and governance principles.
Experience working in Agile/Scrum development environments.
Strong analytical, problem-solving, and troubleshooting skills.
Ability to learn and adapt quickly to new technologies and frameworks.
Experience working with AI agents and AI-assisted development tools for faster development and engineering efficiency.
Strong communication and collaboration skills with cross-functional teams.

Responsibilities

Design, develop, and maintain scalable ETL/data ingestion pipelines for processing large volumes of structured and unstructured data.
Work extensively with SQL and NoSQL databases, particularly MongoDB, to support enterprise data platforms and analytics solutions by Tableau.
Optimize database performance through query tuning, indexing, partitioning, and efficient data modeling techniques.
Process, store, archive, and purge high-volume datasets while ensuring performance, scalability, and reliability.
Develop high-performance data processing solutions using Python and PySpark.
Implement and manage modern data lake/lakehouse architectures using open table formats such as Apache Iceberg and Delta Lake.
Ensure data quality, integrity, validation, and governance across data pipelines and storage systems.
Build and maintain interactive Tableau dashboards and visualizations for business and operational reporting.
Collaborate with cross-functional teams including business stakeholders, analysts, and engineering teams to deliver scalable data solutions.
Work effectively within Agile/Scrum teams, participating in sprint planning, daily stand-ups, backlog grooming, code reviews, and iterative delivery cycles.
Troubleshoot performance bottlenecks and optimize end-to-end data workflows.
Explore, evaluate, and adopt new technologies, frameworks, and best practices in data engineering.
Leverage AI agents and AI-assisted development tools to accelerate proof-of-concepts, automation, and engineering productivity.
Document technical designs, data flows, and operational procedures to support maintainability and knowledge sharing.