Data Engineer

Role & responsibilities

• Develop and maintain efficient ETL (Extract, Transform, Load) pipelines that ingest, process and transform large datasets from diverse sources.
• Build and manage data storage solutions using relational and non-relational databases, ensuring high availability, performance and scalability.
• Work with APIs, third-party data sources and internal databases to create unified datasets that provide actionable insights for business stakeholders.
• Partner with business intelligence analysts, data scientists and software engineers to design and implement data-driven solutions that meet business requirements.
• Design optimized data schemas and structures that support analytical workloads and improve query performance.
• Leverage orchestration tools like Apache Airflow or Prefect to automate ETL workflows and improve operational efficiency.
• Provide technical guidance, review code and promote best practices within the data engineering team.

Preferred candidate profile

• Minimum 8 years of relevant work experience, with at least 4 years focused on designing and developing scalable data pipelines, ETL frameworks and database management systems.
• Bachelors degree (B.E./B.Tech) in Computer Science or IT, or Bachelors in Computer Applications (BCA) from a recognized institution.
• Proficiency in SQL and database technologies such as PostgreSQL, MySQL, Oracle, or SQL Server.
• Hands-on experience with big data frameworks like Apache Spark, Hadoop, or Databricks.
• Strong programming skills in Python, Scala, or Java for data processing and automation.
• Experience with cloud platforms such as AWS, Azure, or GCP, particularly in data services like AWS Glue, Redshift, Big Query, or Snowflake.