Lead Data Engineer - MSS

Tata Consultancy Services; Irvine (CA); On-site; USD 110,000 - 140,000; Full time

Job summary

Tata Consultancy Services is seeking a Lead Data Engineer – MSS in Irvine, CA. The role focuses on hands-on Databricks, dbt, and Python, while leading data platform migration and modernization programs.

Ideal candidates bring 8–15 years of data engineering experience, strong leadership, and a proven track record of delivering enterprise-scale data modernization projects across cloud/on‑prem environments.

Qualifications

• 8–15 years of data engineering experience.
• Experience migrating legacy ETL/data warehouses to modern Databricks Lakehouse.
• Hands-on Databricks, dbt, Python and Spark expertise.

Responsibilities

• Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, and Python.
• Lead migration of legacy data platforms to Databricks Lakehouse.
• Develop and optimize ELT/ETL processes for large-scale ingestion.
• Establish data quality, monitoring, and CI/CD practices.
• Mentor engineers and drive modernization initiatives.

Skills

Leadership

Mentoring

Communication

Tools

Databricks

dbt

Python

PySpark

SQL

Airflow

Delta Lake

Unity Catalog

Databricks Workflows

Structured Streaming

Medallion Architecture

Job description

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 architects, product owners, business analysts, and stakeholders.
• Mentor junior engineers and drive adoption of best practices.

Salary Range- $110,000-$140,000 a year