Lead Data Engineer

Northern Base; Irvine (CA); On-site; USD 170,000 - 260,000; Full time

Job summary

Northern Base is seeking a Lead Data Engineer in Irvine, CA to drive data platform modernization. You will lead hands-on Databricks-based migrations and build robust data pipelines using PySpark, SQL, and Python.

The role combines deep technical work with leadership responsibilities across engineering teams. The ideal candidate will have experience migrating legacy warehouses and ETL ecosystems to modern architectures and possess strong solution design capabilities to deliver enterprise-scale

Responsibilities

• Lead a team of data engineers and developers.
• Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, and Python.
• Lead migration of legacy data platforms to Databricks Lakehouse with modern ELT patterns.
• Develop and optimize ELT/ETL processes for large-scale data ingestion and transformation.
• Establish data lineage, testing, and CI/CD best practices.

Job description

Lead Data Engineer - MSS

Irvine, CA

Fulltime

Job Description

Lead Data Engineer - MSS

Must Have Technical/Functional Skills

Data Bricks , EBT ,Airflow , Asset Management exp

Roles & Responsibilities

Lead Data Engineer MSS

Experience

8 15 Years

Role Overview

We are looking for a highly skilled Lead Data Engineer with strong hands‑on experience in Databricks, dbt, and Python, and a proven track record of leading and executing data platform migration and modernization programs. The ideal candidate will have experience migrating legacy data warehouses, ETL platforms, and cloud/on-prem data ecosystems to a modern Databricks Lakehouse architecture using dbt-based transformation frameworks. This is a hands‑on leadership role requiring deep technical expertise, solution design capabilities, and the ability to mentor engineering teams while driving enterprise-scale data modernization initiatives.

Key Responsibilities

Data Engineering & Development

• Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, and Python.
• Develop and optimize ELT/ETL processes for large-scale data ingestion and transformation.
• Implement robust data quality, monitoring, and reconciliation frameworks.
• Build reusable data engineering components and frameworks.

Data Platform Migration & Modernization

• Lead migration of legacy data platforms, data warehouses, and ETL ecosystems to Databricks Lakehouse.
• Transform existing ETL workloads to modern ELT patterns using dbt.
• Analyze source environments and define migration approaches, roadmap, and execution strategy.
• Drive code conversion, performance optimization, and workload modernization efforts.

Databricks Engineering

Develop solutions leveraging:

• Databricks Lakehouse Platform
• Delta Lake
• Unity Catalog
• Databricks Workflows
• Structured Streaming
• Medallion Architecture (Bronze, Silver, Gold)

Optimize Spark jobs and Databricks workloads for performance and cost efficiency.

dbt Development

• Build and maintain dbt models, macros, tests, and documentation.
• Implement incremental processing and reusable transformation frameworks.
• Establish data lineage, testing, and CI/CD best practices.
• Work closely with business and analytics teams to build trusted datasets.

Leadership & Collaboration

• Lead a team of data engineers and developers.
• Perform code reviews and enforce engineering standards.
• Collaborate with archit ects, product owners, business analysts, and stakeholders.
• Mentor junior engineers and drive adoption of best practices.