Data Engineer

As a Data Engineer, you’ll be part of a team which works with cutting-edge technologies such as Spark, (Scala & Pyspark), python, Databricks, Airflow, SQL, Docker, Kubernetes, and other Data engineering tools.   Responsible to maintianing & assembling data pipelines that consume large datasets, runs the complex data transformations that are needed to generate the facts for the clients. Responsible for integrating finished models into the pipelines that also helps in building the insights for the customer. Use your spark skills to optimize spark code (including data science models). Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using Azure, Databricks and SQL technologies  Write and maintain documentation for features you work on & transition them to L2 support. Minimum 5-8 year of experience as Data engineer.  Experience modeling or manipulating large amounts of data is a must. Hands-on experience as a data engineer  Highly proficient in using the spark framework (python and/or Scala)  Knowledge of Data Warehousing concepts, strategies, methodologies is good to have. Programming experience in Python/scala, SQL. Direct experience of building data pipelines using Apache Spark (Databrics/Fabric), Airflow. Experience with CI/CD & DevSecOps is a plus. Experience with Retail business is a plus  Any cloud certification for Data engineer. Must be team oriented with strong collaboration, prioritization and adaptability skills required  Ability to write efficient code in terms of performance / memory utilization Basic exposure to AI tools will be good to have.