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Tier-1 brand, metro location, mid-level generalist data role and popular tech stack make competition high.
Core data engineering skills (ETL, Airflow, Snowflake, Databricks) are broadly transferable across industries, so sensitivity is low.
Explicit four-year requirement plus specific ETL, Airflow, Snowflake and cloud skills increase shortlisting strictness to high.
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Develop and automate ETL processes using Apache Airflow and Azure Data Factory to optimize data integration pipelines.
Design, maintain, and optimize data architectures including data models and dimensional modeling, ensuring efficient data transformation and validation.
Provide technical guidance and mentor junior team members, support client engagements, and leverage cloud platforms like AWS, Snowflake, and Databricks for scalable data solutions.
Bachelor's degree mandatory.
Minimum 4 years of relevant work experience required.
Proficiency in English (oral and written) mandatory.
Experience with ETL tools (Apache Airflow, Azure Data Factory), cloud platforms (AWS, Snowflake), and database management (MySQL, PostgreSQL) is required as per job responsibilities.
Educational background preferably in Management Information Systems, Computer/Information Science, Systems or Electrical Engineering, Chemical or Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics.
Experience in developing and optimizing data pipelines and integration strategies with strong knowledge of data warehouse indexing and troubleshooting.
Operates effectively within data modernization environments using cloud-based data engineering tools like AWS, Azure Databricks, Apache Airflow, Snowflake, and Databricks platforms.