HTD Talent · 1 day ago
Data Engineering Team Lead
HTD Talent is seeking a Data Engineering Team Lead to guide a team of data engineers in Charlotte, NC. The role involves leading data solutioning, enforcing data modeling standards, and ensuring governance and compliance in data practices.
RecruitingStaffing AgencyTraining
Responsibilities
Lead and mentor a team of data engineers; set expectations, review work, and raise overall engineering quality
Own data solutioning and design decisions, ensuring data is structured correctly from source through analytics and reporting layers
Define and enforce data modeling standards (dimensional modeling, lakehouse/warehouse patterns) to support analytics and machine-learning use cases
Translate business requirements into scalable, well-reasoned data designs that enable reporting and analytical insights
Review code and designs to ensure best practices are followed (reusability, performance, reliability, maintainability)
Guide teams on why solutions are built a certain way, not just how to implement them
Manage delivery across multiple workstreams; track dependencies, unblock teams, and keep initiatives moving
Partner with product owners, program managers, and scrum masters in an agile environment
Ensure governance, security, and compliance standards are met (access controls, data protection, auditing)
Improve DataOps/DevOps maturity, including CI/CD, automation, monitoring, and reliability practices
Qualification
Required
7–10+ years of experience in data engineering, data platforms, or analytics engineering
Prior experience in a technical lead or team lead role, including mentoring engineers and owning design decisions
Strong data solutioning and conceptual data design skills; able to explain how data should be organized to answer business questions
Proven experience with data modeling concepts, including dimensional modeling and designing data for analytics and reporting
Hands-on experience with Databricks / Spark using Python and SQL (depth sufficient to review code, guide implementation, and challenge design decisions)
Strong communication skills with the ability to explain technical concepts clearly to both technical and non-technical stakeholders
Ability to evaluate tradeoffs and recommend solutions aligned to architecture and best practices
Preferred
Azure ecosystem experience (ADLS Gen2, Event Hubs, Key Vault, Private Link/VNet, Managed Identity, Synapse)
Streaming experience (Kafka or Azure Event Hubs)
Power BI semantic model familiarity (security and performance concepts)
Property & Casualty insurance domain experience
Relevant certifications (Azure Data Engineer, Databricks)