Description

You will design, develop, and manage scalable ETL/ELT pipelines for large-scale data ingestion and transformation.

Responsibilities

• Build and maintain data lakes, data warehouses, and data marts on cloud platforms.
• Optimize and monitor data pipelines for performance, reliability, and scalability.
• Implement data quality, governance, and security best practices.
• Write complex SQL queries and perform data modeling to support business intelligence.
• Integrate data from various sources including APIs, databases, and flat files.
• Participate in code reviews and architecture discussions to define team standards.

Required Skills

• 6+ years of experience in data engineering or related roles.
• Proficiency in Python, Scala, or Java for data processing.
• Strong experience with SQL and relational databases such as PostgreSQL and MySQL.
• Hands-on experience with Spark, Hadoop, Hive, and Kafka.
• Deep experience with cloud platforms including AWS (Redshift, S3, Glue, EMR), Azure (Data Factory, Synapse), or GCP (BigQuery, Dataflow).
• Experience with data orchestration tools like Apache Airflow or Prefect.
• Solid understanding of data warehousing concepts, data lakes, and data modeling.
• Familiarity with DevOps practices, Git version control, and CI/CD for data pipelines.
• Any Graduate degree.

Key Skills

Education

Any Graduate