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Senior - Big Data

Job in 400001, Mumbai, Maharashtra, India
Listing for: KPMG India
Full Time position
Listed on 2026-03-05
Job specializations:
  • IT/Tech
    Data Engineer, Big Data
Job Description & How to Apply Below
Job Description

About KPMG in India

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.

KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.

Responsibilities

We're hiring a Spark Scala Developer who has real-world experience working in Big Data environments, both on-prem and/or in the cloud. You should know how to write production-grade Spark applications, fine-tune performance, and work fluently with Scala's functional style.

Experience with cloud platforms and modern data tools like Snowflake or Databricks is a strong plus.

Your Responsibilities

Design and develop scalable data pipelines using Apache Spark and Scala
Optimize and troubleshoot Spark jobs for performance (e.g. memory management, shuffles, skew)
Work with massive datasets in on-prem Hadoop clusters or cloud platforms like AWS/GCP/Azure
Write clean, modular Scala code using functional programming principles
Collaborate with data teams to integrate with platforms like Snowflake, Databricks, or data lakes
Ensure code quality, documentation, and CI/CD practices are followed

Must-Have Skills

3+ years of experience with Apache Spark in Scala
Deep understanding of Spark internals—DAG, stages, tasks, caching, joins, partitioning
Hands-on experience with performance tuning in production Spark jobs
Proficiency in Scala functional programming (e.g. immutability, higher-order functions, Option/Either)
Proficiency in SQL

Experience with any major cloud platform: AWS, Azure, or GCP

Good-to-Have

Worked with Databricks, Snowflake, or Delta Lake
Exposure to data pipeline tools like Airflow, Kafka, Glue, or Big Query
Familiarity with CI/CD pipelines and Git-based workflows
Comfortable with SQL optimization and schema design in distributed environments

Qualifications

B.Tech/ B.E./ Post Graduation
Position Requirements
10+ Years work experience
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