Data Engineer Lead

Position Summary

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.

Duties and Responsibilities

• 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.
• Collaborate with leadership to define key product objectives, KPIs, and performance outcomes.
• Data Platform Ownership
• 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.
• Maintain and communicate enterprise data architecture documentation, including data flows, system dependencies, integration diagrams, platform architecture, and process maps.
• 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.
• 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.
• 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.
• Operational Support & Continuous Improvement
• Assist with internal stakeholder relationships and partner to ensure alignment and best practice implementation (e.g., marketing, contact center, compliance, fraud, risk).
• Manage and coordinate with third-party vendors, implementation partners, and technology providers to support data integrations, platform enhancements, issue resolution, and ongoing operations. Ensure high performance of vendors by monitoring work, evaluating contracts and assessing vendor options.
• Develop and improve monitoring, alerting, support documentation, production readiness, release support, and change management practices. Support testing, QA planning, validation, deployment readiness, and post-implementation review for data-related changes.

Qualifications and Skills

• 5+ years of progressive experience in data engineering, data platform engineering, data warehouse operations, ETL/ELT development, data integration, or related data technology roles.
• 3+ years of experience providing technical leadership, functional work direction, mentorship, solution review, or escalation support for data engineering or technology teams.
• 5+ years of hands-on experience designing, developing, supporting, and optimizing data pipelines, ingestion processes, data conversions, data quality processes, and data loading patterns.
• 5+ years of experience with SQL, relational databases, data modeling, data mapping, data validation, reconciliation, and data analysis.
• 3+ years of hands-on experience administering, supporting, or optimizing Snowflake or comparable cloud data platforms.
• Experience with cloud and/or on-premises database environments, including platform configuration, access management, performance considerations, and operational support.
• Experience with data integration technologies, APIs, middleware, Azure Enterprise Service Bus, or similar integration platforms.
• Experience with development lifecycle practices and tools such as C#, GitHub or similar source control, Azure DevOps, CI/CD pipelines, and deployment management.
• Experience with reporting, analytics, and business intelligence environments such as Cognos, Tableau, Power BI, or similar tools.
• Experience leading or supporting data migration, reporting modernization, platform implementation, and data validation initiatives.
• Demonstrated ability to document and communicate enterprise data architecture, system dependencies, data flows, business rules, technical requirements, process maps, and support procedures.
• Demonstrated ability to translate business needs into scalable, secure, reliable, and well-documented technical data solutions.
• Strong understanding of data governance, data security, data quality, regulatory compliance, and cybersecurity considerations in a financial services environment.
• Bachelor’s degree in Information Technology, Computer Science, Data Analytics, Business Information Systems, Engineering, or a related field, or equivalent combination of education and experience.

Necessary Competencies

• Critical thinking
• Leads Courageously
• Initiative
• Creativity
• Communication
• Organizational Skills
• Interpersonal Awareness
• Decisiveness

Physical Environment

This position is performed in a corporate office (Lakewood, OH), hybrid, or remote setting:

• If fully remote: must be willing to travel
• This position will requires the ability to work flexible days/times including occasionally working beyond normal business hours on an “as needed” basis.
• While performing the duties of this job, the employee is regularly required to lift, walk, stand, sit, bend, reach with hands and arms, climb, push/pull, use hands, and see, hear and speak.
• The employee must occasionally lift and/or move up to 25 pounds.
• The noise level in the work environment is usually quiet to moderate.