Data Manager

General Dynamics Information Technology•Gaithersburg, MD

2d•Hybrid

About The Position

GDIT is seeking a dynamic and experienced Data Manager to guide and oversee critical data initiatives, specifically focused on data migration and synchronization efforts for a major federal health client. This role requires demonstrated hands-on technical experience within the last 3 years and the ability to lead a team of data technologists towards successful project delivery. The ideal candidate will have expertise with Databricks, strong organizational and communication skills, and the ability to bridge technical and business needs seamlessly. This role requires 3-days a week onsite in Gaithersburg, MD. However, candidates who live outside of a 50-miles radius from Gaithersburg, MD and meet all the qualifications will be considered for a remote role.

Requirements

Bachelors and 8+ years of experience managing delivery efforts, including at least 3 years leading teams in data-specific projects.
Proven hands-on technical experience within the last 3 years, ideally in data engineering or data analytics roles.
Proficiency in SQL for data querying, analysis, and troubleshooting.
Experience implementing and working with Databricks for data pipelines and advanced analytics capabilities required.
Demonstrated ability to lead and mentor technical teams effectively.
Strong understanding of data migration, synchronization processes, and integration techniques in enterprise or public-sector environments.
Experience working with Agile, hybrid, or traditional delivery methodologies.
Ability to obtain and maintain a Public Trust with residence in the US 3 out of the last 5 years.

Nice To Haves

Familiarity with federal health agencies (e.g., FDA, NIH, CMS).
Knowledge of data governance, ETL tools, cloud-based platforms, and master data management (MDM) concepts.
Awareness of AI/ML concepts in data engineering and advanced analytics.
PMP, CSM, or related certifications.
Confident interfacing with clients, executive stakeholders, and cross-functional teams.
Strong organizational skills with an ability to structure efforts and prioritize tasks effectively, especially in ambiguous settings.

Responsibilities

Lead and manage a team of data technologists, including data architects, engineers, and analysts, ensuring alignment with project goals and technical strategy.
Foster collaboration and support technical skill development within the team.
Manage and oversee the successful delivery of data migration and synchronization activities as part of an enterprise-wide modernization initiative.
Oversee project timelines, deliverables, risks, and resource planning across technical teams and vendors.
Track and report status updates, issues, and risks to senior leadership and client sponsors.
Collaborate with the team on data pipeline development, integration points, and architecture.
Ensure best practices for data modeling, data quality, lineage, and metadata management are aligned with the overall data strategy.
Support the implementation of Databricks and its ecosystem for batch and streaming data pipelines.
Actively engage in technical analyses and troubleshooting efforts.
Use SQL and Databricks to query, transform, and analyze data as part of quality validation processes or solution design.
Provide input into architectural decisions that align technical solutions with business needs.
Serve as the primary point of contact for internal and client stakeholders regarding data initiatives.
Communicate technical concepts clearly to non-technical audiences, such as executives or client representatives.
Stay informed on trends in AI/ML and data automation, identifying opportunities to incorporate innovative solutions into project delivery.

Benefits

Flexible work schedule supporting work-life balance.
Comprehensive benefits including 401K match and health packages.
Career growth through paid certifications and training opportunities.
Collaborative and mission-driven culture.
The chance to lead high-impact initiatives transforming public health through data-driven decision-making.

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