Data Engineer

Job Title: Data Engineer

Experience:

Location:

Mandatory Skills:

Key Responsibilities

• Design, develop, and maintain

  scalable ETL/ELT pipelines

  to ingest and transform large datasets from diverse sources.
• Build and optimize

  PySpark-based data processing workflows

  for batch and real-time data use cases.
• Write high-performance

  SQL

  queries and manage complex data models for analytics and reporting.
• Collaborate with data architects, analysts, and cross-functional teams to understand business requirements and translate them into technical solutions.
• Ensure

  data quality, accuracy, and reliability

  through robust validation and monitoring frameworks.
• Optimize data storage and processing performance on cloud or distributed systems.
• Implement automation for recurring tasks using

  Python

  and related tools.
• Work with CI/CD pipelines and version control to maintain clean, scalable, and maintainable code.
• Troubleshoot and resolve issues in data pipelines, ensuring minimal disruption to business operations.

Required Skills & Qualifications

• 510 years

  of hands-on experience in

  Data Engineering

  .
• Strong proficiency in

  SQL

  , including complex queries, performance tuning, and data modeling.
• Expertise in

  ETL/ELT development

  , data integration, and transformation frameworks.
• Solid experience in

  PySpark

  for distributed data processing.
• Strong programming experience in

  Python

  , including writing modular, production-grade code.
• Experience working with big data ecosystems (e.g., Hadoop, Hive, Spark).
• Familiarity with data warehousing concepts and cloud platforms (AWS/Azure/GCP).
• Experience with version control (Git), CI/CD, and workflow orchestration tools (Airflow/Luigi) is a plus.
• Strong analytical, problem-solving, and communication skills.