Senior Data Engineer

Bridgestone Americas; Bengaluru Urban; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

Bridgestone Americas is seeking a senior Data Engineer to design, build, and operate industrialized data pipelines across cloud environments. You will act as the Databricks SME, handling Delta Lake models, Unity Catalog governance, and cross-team reviews.

You will mentor juniors, contribute to architecture decisions, and collaborate with BI teams to deliver well- modeled data products for reporting and conversational analytics. This role emphasizes governance with self-service velocity.

Qualifications

• Experience guiding and mentoring other data engineers.
• Proven ability to design and review data pipelines for scale and governance.
• Strong knowledge of Databricks platform components and best practices.

Responsibilities

• Designs, builds, and operates industrialized data ingestion and transformation pipelines.
• Serves as Databricks SME with data modeling in Delta and governance via Unity Catalog.
• Mentors, coaches, and conducts design and code reviews to enforce standards.
• Builds pipelines across AWS and Azure; plans migration of native pipelines to Databricks.
• Defines guardrails and reusable patterns balancing velocity and governance.
• Partners with BI/analytics teams to deliver curated data products for reporting and conversational queries.

Skills

Databricks

Spark

Delta Lake

Unity Catalog

AWS

Azure

Data modeling

Mentoring

ETL pipelines

Tools

Databricks

AWS

Glue

Step Functions

Redshift

Aurora

S3

Data Factory

ADLS

Job description

• Designs, builds, and operates industrialized data ingestion and transformation pipelines from source systems through the silver layer of a medallion architecture, using Databricks (Spark, Unity Catalog, workflows) as the core platform.
• Serves as the team's Databricks subject matter expert — data modeling in Delta, job and cluster design, performance and cost tuning, and Unity Catalog governance patterns.
• Guides, coaches, and technically mentors other Data Engineers; conducts design and code reviews to ensure architecture, platform, and solution standards are followed.
• Builds and maintains pipelines across multiple clouds — primarily AWS (Glue, Step Functions, Redshift, Aurora, Transfer Family, S3) and Azure (Data Factory, ADLS) — and plans the migration of native cloud pipelines to Databricks as a destination technology.
• Defines and enforces the guardrails, standards, and reusable patterns that business units follow when building their own projects on the platform, balancing self-service velocity against governance requirements.
• Partners with the BI and analytics teams to deliver curated, well-modeled, well-documented data products fit for reporting and for conversational query experiences such as Databricks Genie Space.