IN_Manager_Databricks Data Engineer_GCC_Advisory_Bangalore

PwC International

Bengaluru

On-site

INR 3,000,000 - 4,500,000

Full time

3 days ago

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Job summary

PwC Bengaluru is seeking an experienced Data Engineer – Databricks to design, build, and operate scalable data pipelines on the Databricks Lakehouse Platform, leveraging Spark, Delta Lake and cloud-native services. You will work closely with analytics, AI/ML, and business teams to deliver data-driven insights.

The role requires 7+ years of data engineering experience, strong SQL, and hands-on Databricks expertise.

Qualifications

7+ years of experience as a Data Engineer with Databricks expertise.
Hands-on with Apache Spark, PySpark, and Spark SQL.
Strong knowledge of Delta Lake and Lakehouse architecture.
Advanced SQL skills and data warehousing concepts.

Responsibilities

Design, build, and maintain end-to-end data pipelines on Databricks.
Ingest, transform, and curate large-scale datasets.
Collaborate with analytics, AI/ML teams, and business stakeholders.
Ensure data quality, lineage, and governance.
Provide production support and troubleshoot data pipelines.
Document designs and runbooks.
Mentor junior engineers and contribute to best practices.

Skills

Databricks

Apache Spark

Spark SQL

Delta Lake

SQL

Cloud platforms (Azure/AWS/GCP)

Agile methodologies

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Tools

Snowflake

Unity Catalog

Job description

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager Job Description & Summary At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us. At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.

Job Description & Summary

We are seeking an experienced Data Engineer – Databricks to design, build, and operate scalable, high-performance data pipelines on the Databricks Lakehouse Platform. The role involves hands‑on development using Apache Spark, Databricks notebooks, Delta Lake, and cloud-native services, along with close collaboration with analytics, AI/ML, and business teams.

Responsibilities

Design, build, and maintain end-to-end data pipelines using Databricks (PySpark / Spark SQL)
Implement batch and incremental data processing using Delta Lake and multi-hop architecture
Develop and optimize Databricks notebooks, jobs, and workflows
Ingest, transform, and curate large-scale structured and semi-structured datasets
Support analytics, reporting, and downstream data consumption use cases
Ensure data quality, reliability, lineage, and governance
Collaborate with data scientists, analysts, and architects on AI/ML workloads
Optimize Spark jobs for performance and cost efficiency
Adhere to enterprise security, access control, and compliance standards
Provide production support and troubleshoot data pipeline issues
Document technical designs, data flows, and operational runbooks
Mentor junior engineers and contribute to best practices

Mandatory skill sets