Lead Data Engineer

**We CANNOT work with third party C2C employers. Candidates must be GC or USC to be considered.**

This role is for an Engineering Leader who will guide a small, high-performing team of data engineers, analysts, and BI developers within a large enterprise data organization. The focus is on delivering impactful data and analytics projects, including building data pipelines, modernizing legacy systems, and delivering executive dashboards. The right candidate combines strong technical leadership with hands-on abilities, ensuring seamless project execution from strategy to delivery

.Top 4 Skills

1. :Data Engineering Leadership – Proven experience managing and mentoring technical teams
2. .Modern Data Stack Expertise – Snowflake, SQL, Python, ETL tools (dbt, Airflow)
3. .BI & Analytics Development – Experience with Power BI, Tableau, or similar tools
4. .Enterprise Data Strategy Alignment – Strong stakeholder communication and alignment with business goals

.Responsibilities

• :Lead and mentor a small cross-functional team handling 3–4 simultaneous projects
• .Own project delivery from design through deployment
• .Engage in technical architecture and problem-solving discussions
• .Oversee projects involving
• :Data pipeline development and optimization
• .BI dashboard creation and maintenance
• .Modernization of legacy data/reporting systems
• .Supporting ad-hoc requests from leadership
• .Collaborate with leadership to align tech work with business strategy
• .Promote best practices in engineering and data operations

.Qualifications

• :7 years in software/data engineering, including 2 years in a lead role
• .Proficient in Snowflake, SQL, Python, and modern ETL tools (dbt, Airflow)
• .Experience with BI tools like Power BI, Tableau, or Looker
• .Strong multitasking skills with the ability to balance strategic and tactical work
• .Excellent communicator with proven stakeholder collaboration experience
• .Ability to lead remote teams effectively and foster team growth

.Preferred

• :Experience with cloud platforms (GCP, AWS, Azure)
• .Background in enterprise digital/data transformations
• .Exposure to ML or data science pipelines is a plus