Data Engineering Technical Lead (TS/SCI with Poly Required)

GCI embodies excellence, integrity and professionalism. The employees supporting our customers deliver unique, high-value mission solutions while effectively leverage the technological expertise of our valued workforce to meet critical mission requirements in the areas of Data Analytics and Software Development, Engineering, Targeting and Analysis, Operations, Training, and Cyber Operations. We maximize opportunities for success by building and maintaining trusted and reliable partnerships with our customers and industry.

Duties

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

As the Technical Lead, this position encompasses leading engineering teams at all levels (junior, mid, senior), partnering with clients to clarify mission and technical needs, and architecting future-focused solutions that drive scalability, innovation, sustainable system design, and long-term architectural strength.

The Data Engineer will manipulate data and data flows for both existing and new systems. Additionally, they will provide support in the areas of data extraction, transformation and load (ETL), data mapping, analytics, operations, database design, and maintenance of data and associated systems. As a lead member of the team, the candidate will work in a multi-tasking, quick-paced, dynamic, process-improvement environment that requires experience with the principles of large-scale (terabytes) database development, large-scale file manipulation, data modeling, data mapping, data testing, data quality, and documentation preparation.

Key Responsibilities

• Develop data management strategies and architect scalable, cloud‑ready, and future‑oriented big data solutions.
• Engage in direct client interactions to present technical strategies, risks, and implementation plans.
• Evaluate emerging technologies to drive innovation and mission impact.
• Establish engineering standards and promote continuous improvement.
• Ability to complete milestones and work toward multiple deadlines simultaneously.
• Compile and organize statistical information retrieved and present finding to management.
• Translate technical information into clear, readable documentation and presentations to be used by technical and non-technical personnel.
• Research and evaluate sources of information to determine possible limitations in reliability or usability.
• Lead requirements‑gathering and clarification sessions with clients and stakeholders.
• Mentor and oversee data engineers, software developers, and/or DevOps engineers, ensuring quality, consistency, and adherence to engineering best practices.
• Provide support in the areas of data extraction, transformation and load (ETL), data mapping, analytics, operations, databases, and maintenance of data and associated systems.
• Develop and manage complex data flows, or makes significant enhancements to existing pipelines.
• Troubleshoot complex problems and provide customer support for the ETL process.
• Advise hardware and/or cloud engineers on machine characteristics that affect software systems, such as storage capacity, processing speed, and input/output requirements.
• Conduct investigations and tests of considerable complexity.
• Provide ongoing maintenance, support, and enhancements in existing systems and platforms.
• Collaborate cross-functionally with software engineers, data scientists, analysts, project managers and other engineering groups.
• Research emerging technologies to determine impact on application execution.
• Communicate clearly and effectively with teammates, customers, and external partners.
• Prepare written and verbal communications on analyses, findings, and project progress.
• Write and update technical documentation such as user manuals, system documentation, training materials, processes and procedures.
• Provide recommendations for continuous improvement.
  
  

Education And Experience

Bachelor's degree in Computer Science, Information Technology, or other related technical discipline, or equivalent combination of education, technical certifications, training, and 10 years of data management and/or engineering experience. Additional years of experience in lieu of degree

Required Qualifications

• Proven experience providing technical leadership to cross-functional engineering teams, including setting architectural direction, establishing engineering standards, and translating complex mission needs into actionable technical roadmaps.
• Demonstrated ability to engage directly with clients, stakeholders, and program leadership to communicate technical concepts, influence decision-making, and guide requirements definition.
• 5 years of hands-on experience with Big Data ecosystems, including large-scale data ingestion, processing, cleansing, analysis, and performance optimization across distributed environments.
• Advanced expertise with modern big data platforms and query engines such as Hadoop (AWS), Spark, Presto/Trino, or AWS Athena, with the ability to evaluate trade-offs and architect scalable solutions.
• Deep experience designing, managing, and optimizing large-scale data stores, including data lakes, data warehouses, relational databases (Postgres, MySQL, SQL Server), and distributed or NoSQL storage systems.
• Demonstrated success leading teams through the detailed analysis and operationalization of large, complex datasets in mission-critical production environments.
• Proficiency with enterprise search and indexing technologies, including Elasticsearch or OpenSearch, with the ability to design and optimize search-driven data workflows.
• Extensive experience overseeing ETL development, data integration, and migration efforts, as well as leading teams in the adoption of orchestration and ingest tools such as Dagster, Airflow, NiFi, or Spark Streaming.
• Strong automation and engineering fundamentals, with scripting capabilities in Python, Bash, and Shell to ensure consistency, quality, and operational efficiency across data pipelines.
• Demonstrated experience developing technical roadmaps and long-term data-engineering strategies that align with organizational goals and guide the evolution of enterprise data platforms.
• Proven ability to evaluate, select, and operationalize emerging technologies, integrating innovative capabilities into production systems to enhance scalability, performance, and mission impact.
• Strong ability to influence architectural direction across teams and programs, ensuring alignment with best practices, enterprise standards, and overarching technical strategy.
• Experience researching and evaluating sources of information to determine possible limitations in reliability or usability
  
  

Desired Qualifications

• Prior technical leadership, mentorship responsibilities, or experience directing others in engineering activities.
• Experience with different file formats like ORC, Parquet, AVRO, JSON.
• Experience in system management expertise with monitoring, disaster recovery, backup, automated testing, automated schema migration, and continuous deployment.
• Exposure in Infrastructure as Code languages like Amazon CDK and CloudFormation.
• Experience in Agile software methodologies.
• Certified Data Management Professional
• 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