Senior Data Engineer

• Drive data engineering efforts to deliver enterprise-wide capabilities and complex data solutions
• Direct code design and delivery for data integration, cleaning, transformation, and control across operational and analytical systems
• Work with Project Management to define outcomes and inform work structures
• Provide technical thought leadership for complex data solutions across systems and domains
• Lead design, governance, and continuous improvement of structured and unstructured data and knowledge foundations supporting AI and agentic capabilities across Network Services
• Define standards, guidelines, guardrails, and controls for documentation, configurations, telemetry, metadata, policies, standards, and operational knowledge
• Partner with product and service subject matter experts to translate network and operational knowledge into reusable AI-ready assets
• Design scalable methods for storing, governing, indexing, validating, and retrieving AI context assets
• Establish preventative and detective controls for data, metadata, knowledge, lineage, and freshness quality
• Define ownership, stewardship, lineage, freshness, governance, and control accountability
• Build or guide pipelines, transformations, validation routines, metadata structures, and supporting services
• Assemble and maintain complex data sets and processes for transformation, data structures, metadata, quality controls, dependencies, and workload management
• Design and develop data architecture using multiple architectural components
• Define and build data pipelines for data-informed decision-making
• Contribute to integration, regression, and performance test suites; analyze reports and lead issue triage
• Identify gaps in data management standards and develop plans to close them
• Conduct concept testing and research to prototype toolsets and improve processes
• Mentor Data Engineers in continuous integration and continuous delivery
• Define key performance indicators and internal controls

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or related field
• 7+ years of experience in data engineering, with demonstrated leadership in enterprise data platforms
• Advanced proficiency in SQL and Python
• Deep expertise in data integration, pipeline development, and large-scale data processing
• Strong experience implementing data quality frameworks and automated validation
• Advanced knowledge of data modeling, metadata, and lifecycle management
• Experience with data governance, lineage, and control frameworks
• Strong understanding of AI/ML data requirements and data readiness practices
• Proven ability to design solutions for scalable, high-performance analytics platforms
• Experience enabling AI-ready data ecosystems and advanced analytics platforms
• Demonstrated success implementing enterprise data quality programs and governance frameworks
• Strong knowledge of Data Ops and MLOps practices
• Experience designing and supporting hybrid (cloud + on-prem) data architectures
• Background in regulated industries with audit, risk, and compliance requirements
• Proven track record of driving data strategy and platform modernization initiatives
• Ability to work 1st shift in the United States of America
• 40 hours per week

Demonstrates expertise in data engineering, focusing on data integration, pipeline development, and governance frameworks. Proven ability to design scalable data architectures and implement data quality programs to support AI and advanced analytics initiatives.

• Data Engineering Leadership
• Advanced SQL Proficiency
• Python Programming
• Data Governance Frameworks
• Data Ops and MLOps Practices

• Data Integration
• Pipeline Development
• Data Quality Frameworks
• Data Modeling
• Metadata Management
• Large-Scale Data Processing
• AI/ML Data Requirements
• Hybrid Data Architectures
• Data Strategy Implementation
• Performance Analytics Design

• Technical Thought Leadership
• Mentoring Data Engineers
• Collaboration with Subject Matter Experts

• Enterprise Data Platforms
• Regulated Industries
• Audit and Compliance
• Data Freshness Quality
• Operational Knowledge