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Data Engineer

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Onsite

Data Engineer

Walking Tree

Data Engineer

Skills

SQL QueriesTableauPythonKafkaAWSPySparkApache AirflowCompliancePower BITerraform

1 month ago

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Important information


Contract type:

Permanent

Location:

Nagpur, Maharashtra, India

Work mode:

Onsite

Published on:

23 September 2026

What they need


Job Details:-

Location: Gurugram (Work From Office)
Experience: 6+ Years

Job Summary

We are seeking a highly skilled Data Engineer with 6+ years of experience and strong hands-on expertise in PySpark, AWS, and Python to build and maintain scalable, high-performance data pipelines. The role involves working on large-scale distributed data processing systems and delivering reliable data solutions to support analytics and business intelligence.

Key Responsibilities

  • Design, develop, and optimize ETL/ELT pipelines using Python and PySpark
  • Build and maintain large-scale data processing frameworks on AWS
  • Develop batch and near-real-time data pipelines
  • Process structured and semi-structured data using Apache Spark
  • Ingest data from multiple sources including APIs, databases, and streaming platforms
  • Optimize Spark jobs for performance and cost efficiency
  • Build and manage data lakes using AWS S3
  • Implement data workflows using orchestration tools (Airflow, AWS Glue, Step Functions)
  • Ensure data quality, validation, and reliability
  • Monitor production pipelines and resolve failures
  • Collaborate with data scientists, analysts, and business stakeholders
  • Follow best practices for security, governance, and compliance on AWS

Required Skills & Qualifications

  • 6+ years of experience as a Data Engineer

  • Strong proficiency in Python and PySpark

  • Hands-on experience with AWS services, including:

  • S3, EC2, EMR, Glue, Lambda

  • Redshift, Athena

  • CloudWatch, IAM

  • Strong experience with Apache Spark and distributed data processing

  • Advanced SQL skills for querying and data transformation

  • Experience with ETL tools and frameworks

  • Experience with data warehousing and data modeling

  • Strong understanding of data partitioning, performance tuning, and cost optimization

  • Experience with Git and CI/CD pipelines

Good to Have / Preferred

  • Experience with streaming technologies (Kafka, Kinesis)
  • Knowledge of Delta Lake / Iceberg / Hudi
  • Experience with Terraform or CloudFormation
  • Exposure to BI tools (Power BI, Tableau, QuickSight)
  • Experience supporting production data systems in enterprise environmentsRole & responsibilities

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