Data Engineer

We are looking for a Data Engineer to build and manage scalable data solutions for the Consumer Packaged Goods (CPG) domain. This role plays a key part in ensuring data accuracy, system performance, and smooth integration across platforms. The work you do will help generate insights into consumer behaviour, demand forecasting, and supply chain efficiency, enabling better business decisions.
Responsibilities:
Design, build, and maintain scalable data pipelines (extract, load, clean, transform, ingest).
Develop and maintain production-grade Spark and PySpark pipelines.
Build and deploy workflows using orchestration tools like Airflow or Kubeflow.
Own and manage multiple data pipelines end-to-end.
Monitor, review, and improve pipeline performance and reliability.
Implement real-time monitoring and alerting for data systems.
Collaborate with AI/ML engineers, DevOps, and product teams to solve business problems.
Create technical documentation, including HLDs and LLDs.
Follow modular and configurable coding practices.
Support maintenance activities, including bug fixes and performance optimisation.
Requirements:
3-6 years of experience in Data Engineering.
Strong coding skills in Python, PySpark, and SQL.
Hands-on experience with Apache Spark in production environments.
Experience building and supporting scalable ETL pipelines.
Familiarity with Airflow or Kubeflow for workflow orchestration.
Experience working with AWS or Azure.
Knowledge of big data infrastructure and data modelling.
Experience in performance tuning and data ingestion optimisation.
Familiarity with developer tools such as GitHub, Docker, and VSCode.
Ability to work in a fast-paced environment and manage deadlines.

Experience
3-6 yrs