Data Engineering Lead

Description

The Data Engineering Lead plays a critical and strategic role in advancing FMHC’s enterprise data transformation and analytics enablement efforts. This role provides technical leadership, direction, and oversight for data engineering activities across data platforms, data pipelines, integrations, data warehouse operations, middleware/Azure Enterprise Service Bus capabilities, reporting modernization, and enterprise data governance practices.

In partnership with business stakeholders and third-party vendors, the Data Engineering Lead is responsible for guiding the design, development, support, and continuous improvement of scalable, secure, reliable, and well-documented data solutions. This role provides day-to-day technical direction to Data Engineer I and Data Engineer II roles, supports their professional development, and serves as a primary escalation point for complex technical, operational, and data quality issues.

• Leadership & Strategic Oversight.
• Lead and mentor a team of Data Engineering and Analyst staff, providing coaching, performance feedback, and professional development opportunities.
• Serve as the primary escalation point for complex data engineering, data platform, integration, data quality, and production support issues.
• Establish and communicate data engineering standards, best practices, development patterns, documentation expectations, and operational procedures.
• Lead regular technical planning, solution review, and prioritization discussions to ensure timely execution of data engineering initiatives.
• Promote a collaborative, high-performing team culture focused on accountability, quality, continuous improvement, operational excellence, and knowledge sharing.
• Support professional development of data engineering team members through coaching, feedback, technical guidance, and skill development opportunities.
• Serve as the primary escalation point for team-level challenges, providing guidance, resolution, and technical mentorship as needed.
• Collaborate with leadership to define key product objectives, KPIs, and performance outcomes.

• Lead and assist in administration, optimization, and operational oversight of Snowflake and related cloud data platforms.
• Oversee table structures, role and permission management, performance tuning, cost optimization, capacity planning, and platform configuration standards.
• Provide leadership for Data Warehouse, Middleware/Azure Enterprise Service Bus, Cognos, Limagito, and related analytics platform operations.
• Ensure data platforms are scalable, secure, reliable, cost-effective, and aligned with business and technology goals. Recommend, implement, and maintain best practices for data platform engineering, platform operations, and environment management.
• Oversee bug tracking, error resolution, and continuous optimization.
• Design, implement, and oversee intake and delivery processes related to Business Intelligence, Analytics, Reporting, and Data Provider sourcing initiatives.
• Translate product roadmap features into well-defined requirements, user stories, and acceptance criteria.
• Support creation of test scripts, QA planning, and post-launch performance tracking.
• Data Pipeline, Integration & Architecture Leadership
• Lead and assist in implementing the design, development, implementation, and support of scalable data pipelines, data conversions, ingestion processes, integrations, and data vendor feeds.
• Oversee data extraction, ingestion, transformation, normalization, anonymization, validation, loading, and reconciliation processes.
• Guide integration activities involving APIs, middleware, Azure ESB, core banking systems, digital banking platforms, and third-party data sources.
• Maintain and communicate enterprise data architecture documentation, including data flows, system dependencies, integration diagrams, platform architecture, and process maps.
• Data Quality, Governance, Security & Compliance
• Lead the implementation and continuous improvement of data validation, reconciliation, monitoring, and quality control processes.
• Establish standards for data quality checks, issue tracking, data lineage, data mappings, business rules, and data documentation.
• Enforce data governance policies to ensure data is secure, consistent, accurate, reliable, and compliant with applicable financial regulations and cybersecurity standards.
• Ensure appropriate controls are considered in data access, data sharing, reporting, integration, and platform administration processes.
• Operational Support & Continuous Improvement & Non-Technical Ownership
• Assist with internal stakeholder relationships and partner to ensure alignment and best practice implementation (e.g., marketing, contact center, compliance, fraud, risk).
• Oversee and track project and program roadmaps, identifying risks, dependencies, and cross-functional impact. Lead backlog prioritization in alignment with business goals and customer feedback.
• Manage and coordinate with…