Job Description
Databricks Lead Data Engineer
Full Time
US - Remote
Salary Range: $200,000 To $260,000 Annually
Databricks Lead Data Engineer – K2 Insurance Services - Remote
Founded in 2011, K2 Insurance Services, LLC is a results-driven managing general agency offering specialty insurance programs through retail and wholesale channels. With over 40 active programs and 20,000+ distribution partners, K2 provides innovative, customized solutions across niche markets
K2 Insurance Services, LLC seeks a full-time Lead Databricks Data Engineer to spearhead our data engineering initiatives, focusing on designing, building, and optimizing scalable data solutions using Databricks. As a lead, you will mentor a team of data engineers, collaborate with cross-functional stakeholders, and define best practices to unlock the full potential of our data.
K2 Insurance Services offers the opportunity to join an established company in growth mode. Our compensation program includes competitive pay; bonus plan; medical, dental, and vision insurance; paid time-off in year of hire; and 401(k) with employer match.
Salary Range: $200,000 To $260,000 USD per year
Key Responsibilities:
Leadership & Strategy:
Lead and mentor a team of data engineers in implementing Databricks-based solutions.
Define and drive the data engineering strategy, ensuring alignment with business goals.
IT Product Owner role for organizational data warehouse project.
Databricks Expertise:
Design and develop scalable data pipelines and ETL processes using Databricks.
Optimize and tune Spark jobs for performance and efficiency.
Develop and enforce best practices for Databricks cluster management and data security.
Data Architecture:
Build and maintain robust data models to support analytics and reporting needs.
Integrate Databricks with various data sources (cloud storage, databases, APIs).
Implement Delta Lake for reliable, scalable, and performant data lakes.
Collaboration:
Work closely with data scientists, analysts, and stakeholders to deliver actionable insights.
Act as the technical liaison between the data engineering team and other stakeholders.
Innovation & Optimization:
Stay updated on the latest Databricks and Azure features to drive continuous improvements.
Automate repetitive processes and streamline data workflows.
Qualifications:
Preferred Skills: