Data Engineer

Grid Dynamics

Bengaluru

Hybrid

INR 900,000 - 1,400,000

Full time

3 days ago
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Job summary

Grid Dynamics is seeking a Data Engineer to design and implement scalable data pipelines using Hadoop, PySpark, Python, Airflow and AWS. The role focuses on enabling analytics and data science teams with robust data infrastructure.

The responsibilities include building ETL/ELT workflows, data processing at scale, and collaborating with data scientists to deliver robust data solutions. You will optimize pipelines, ensure data quality and reliability in production, and contribute to design,

Qualifications

  • Hands-on experience with Hadoop, PySpark, Python, Airflow, and AWS.
  • Experience building ETL/ELT pipelines and processing large datasets.
  • Good knowledge of SQL and distributed data processing.

Responsibilities

  • Build and maintain scalable data pipelines using Hadoop, PySpark, Python, and Airflow.
  • Develop ETL/ELT workflows for processing large-scale datasets.
  • Collaborate with product owners, business stakeholders, and data scientists to deliver data solutions.
  • Automate recurring data processes and optimize existing data engineering workflows.
  • Ensure data quality, performance, and reliability across production environments.
  • Participate in system design, development, testing, deployment, and ongoing support.

Skills

SQL
Agile development
Data quality

Tools

Hadoop
PySpark
Python
Airflow
AWS

Job description

We are looking for a Data Engineer with hands-on experience in Hadoop, PySpark, Python, Airflow, and AWS to build scalable data pipelines and support enterprise data platforms. The ideal candidate should be experienced in developing, optimizing, and maintaining data engineering solutions that enable analytics and data science teams.


Key Responsibilities

  • Build and maintain scalable data pipelines using Hadoop, PySpark, Python, and Airflow.
  • Develop ETL/ELT workflows for processing large-scale datasets.
  • Collaborate with product owners, business stakeholders, and data scientists to deliver data solutions.
  • Automate recurring data processes and optimize existing data engineering workflows.
  • Ensure data quality, performance, and reliability across production environments.
  • Participate in system design, development, testing, deployment, and ongoing support.

Mandatory Skills

  • Strong hands-on experience with Hadoop, PySpark, Python, Airflow, and AWS.
  • Experience building ETL/ELT pipelines and processing large datasets.
  • Good knowledge of SQL and distributed data processing.
  • Experience with workflow orchestration and production support.
  • Understanding of data engineering best practices and Agile development.

Good to Have

  • AWS services such as S3, EMR, Glue, Lambda, or Redshift.
  • Spark optimization and performance tuning.
  • CI/CD and Git.
  • Experience working with data scientists and analytics teams.
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