Data Engineer

Description
Lead Data Engineer
Salary: Up to $160,000 Location:
On-Site | South Los Angeles Area
Employment Type: Full-Time
Build the Foundation for Enterprise Analytics
We are seeking a Lead Data Engineer to drive the architecture, modernization, and expansion of a growing enterprise data platform built within the Microsoft Azure ecosystem. This is a highly visible technical leadership role where you'll help shape the future of data across multiple business functions by building scalable, secure, and high-performing data solutions.
If you're passionate about Databricks, cloud data platforms, and mentoring engineering teams while remaining hands-on with development, this is an opportunity to make a significant impact.
What You'll Do

• Lead the design, implementation, and optimization of an enterprise Azure Databricks Lakehouse environment utilizing Bronze, Silver, and Gold data layers.
• Architect and execute migrations from SQL Server and legacy platforms into modern cloud-native data solutions.
• Develop and optimize large-scale ETL/ELT pipelines supporting operational reporting, business intelligence, advanced analytics, and data science initiatives.
• Integrate data from multiple enterprise systems, APIs, operational platforms, and third-party sources.
• Establish best practices for data engineering, data modeling, testing, CI/CD, monitoring, governance, and production support.
• Implement and maintain data governance frameworks, security controls, lineage tracking, and access management.
• Lead code reviews, technical design discussions, and engineering standards across the data team.
• Mentor and support data engineers while fostering a culture of technical excellence.
• Partner closely with business stakeholders, analysts, and data scientists to deliver trusted, scalable data products.

For immediate consideration, apply now and direct message Reid Gormly on LINKEDIN
Requirements
Required Qualifications

• 5+ years of Data Engineering experience.
• 3+ years of hands-on production experience with Databricks and Apache Spark.
• Strong technical leadership experience, including architecture ownership and mentoring engineers.
• Advanced proficiency in Python, PySpark, and SQL.
• Experience with:
• Azure Databricks
• Azure Data Lake Storage (ADLS Gen2)
• Delta Lake
• Databricks Workflows or Lakeflow Jobs
• Strong understanding of medallion architecture and modern data lakehouse design.
• Experience migrating enterprise workloads from SQL Server or similar database platforms to the cloud.
• Expertise with data quality frameworks, monitoring, alerting, reconciliation processes, and disaster recovery strategies.
• Experience with Git-based development workflows, automated testing, and CI/CD deployment pipelines.
• Excellent communication skills with the ability to explain technical decisions to both technical and non-technical audiences.

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