Data Engineer

TymblHub; Pune District; On-site; INR 2,000,000 - 7,000,000; Full time

Job summary

Epam Systems in Pune, India is seeking a Data Engineer with strong Spark, Python, and cloud-based data platforms. You will design, develop, and optimize data pipelines for BI and analytics, leveraging AWS, Databricks, and GCP.

You will build ETL/ELT workflows, ensure data quality, security, and governance, and collaborate with data scientists and stakeholders to deliver scalable data solutions.

Qualifications

• We require 5+ years of data engineering experience with scalable pipelines.
• Hands-on with Spark, Python, and cloud data platforms (AWS Databricks, GCP).
• Experience designing, developing, and optimizing ETL/ELT workflows.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Spark and Python.
• Build and optimize batch and distributed data processing applications.
• Implement ETL/ELT workflows for ingestion, transformation, and integration.
• Utilize AWS, Databricks, and GCP for data processing and storage.
• Ensure data quality, monitoring, and security across pipelines.

Skills

Apache Spark

Python

ETL/ELT pipelines

Tools

AWS Databricks

Google Cloud Platform (GCP)

Databricks

Job description

# Data EngineerEpam SystemsPosted on October 19, 2026---Experience5 - 15 yrsSalary (CTC)₹20L - ₹70LJob LocationPune, IndiaVacancy10DesignationData EngineerJob TypeNot specified---## Job Description**Job Summary**We are looking for a skilled Data Engineer with strong expertise in Apache Spark, Python, and cloud-based data engineering platforms. The ideal candidate will have hands-on experience developing scalable data pipelines, processing large datasets, and implementing data solutions on AWS, AWS Databricks, and Google Cloud Platform (GCP).The candidate will be responsible for designing, developing, optimizing, and maintaining robust data processing workflows to support business intelligence, analytics, and data-driven applications.**Key Responsibilities*** Design, develop, and maintain scalable data pipelines using Apache Spark and Python.* Build and optimize batch and distributed data processing applications.* Develop ETL/ELT workflows for data ingestion, transformation, cleansing, and integration.* Implement data engineering solutions using AWS cloud services and Databricks.* Develop and manage data processing workflows on Google Cloud Platform (GCP).* Optimize Spark jobs for performance, scalability, resource utilization, and cost efficiency.* Work with structured, semi-structured, and unstructured datasets.* Implement data quality checks, error handling, logging, and monitoring.* Collaborate with data scientists, analysts, architects, and business stakeholders.* Follow best practices for data security, governance, access control, and cloud resource management.* Troubleshoot production issues and ensure the reliability and availability of data pipelines.