DATA ENGINEER

Responsibilities: ·      Design, develop, and maintain data pipelines to ingest, transform, and serve data from multiple sources. ·      Support batch and near-real-time data processing, ensuring data accuracy, freshness, and reliability. ·      Assist in managing and optimizing data lakes, lakehouses, and data warehouses. ·      Develop and optimize SQL and Python-based transformations for reporting and analytics. ·      Implement basic data quality checks, logging, and monitoring. ·      Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements. ·      Participate in code reviews, testing, documentation, and CI/CD processes. ·      Continuously learn and adopt modern data engineering and AI-enabled data practices. Key Technical Skills & Responsibilities ·      Strong working knowledge of Python and SQL for data processing. ·      Experience building ETL/ELT pipelines using industry-standard practices. ·      Familiarity with cloud data platforms such as: ü Snowflake ü Microsoft Fabric (OneLake, Lakehouse, Data Pipelines) ü AWS(Redshift, Glue) / Azure Data Lake / Google BigQuery ·      Understanding of data modeling concepts (fact/dimension tables, star schema). ·      Experience or exposure to orchestration and transformation tools such as Airflow, DBT, Spark, or Dask. ·      Working knowledge of Git and CI/CD pipelines. ·      Exposure to BI and visualization tools such as Power BI or Apache Superset. ·      Basic understanding of cloud security, access control, and cost optimization. Eligibility Criteria: ·      Bachelor’s degree in computer science, Engineering, or a related discipline. ·      3+years of hands-on experience in data engineering or a closely related role. ·      Experience supporting or maintaining production data pipelines. ·      Strong problem-solving skills and eagerness to learn new technologies. ·      Good written and verbal communication skills. ·      Ability to work effectively in a collaborative team environment.