Data Engineer

About the role

We are looking for a Data Engineer with 2–4 years of hands‑on experience to design, develop, and maintain robust data pipelines. The role focuses on transforming raw data into actionable insights using modern big‑data technologies and cloud platforms.

Key responsibilities

• Develop, test, and optimise ETL/ELT pipelines for both structured and unstructured data.
• Clean, transform, and manipulate data using Python and Pandas.
• Process large datasets with PySpark/Apache Spark and integrate streaming data via Apache Kafka or similar technologies.
• Design and implement data models, data warehouses, and ensure data quality standards.
• Create dashboards and reports using Power BI and/or Looker.
• Collaborate with cross‑functional teams to support analytics workloads on Databricks.
• Maintain version control using Git and follow best practices for code deployment.

Required profile

• 2–4 years of professional experience in data engineering or data analytics.
• Strong programming skills in Python (mandatory).
• Proven ability to work with large‑scale data processing frameworks (Spark, Kafka).
• Experience building and maintaining production‑grade data pipelines.
• Familiarity with cloud environments such as Azure, AWS, or GCP is preferred.

Required skills

• Python
• Pandas
• PySpark / Apache Spark
• Apache Kafka
• SQL (complex queries, joins, stored procedures)
• Databricks
• Power BI
• Looker
• Data modeling and data warehousing
• Git / version control
• Azure, AWS, GCP (preferred)