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Mid-level data engineer, metro locations, broad skillset requirements create high competition.
Core data engineering skills transfer across industries but require platform-specific experience, so medium.
Explicit 6+ years requirement plus mandatory Databricks/PySpark/Azure skills increases shortlisting strictness to high.
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Develop and maintain Modern Data Warehouse solutions using Databricks and AWS/Azure stack.
Collaborate with DW/BI leads and business teams to design, build, and troubleshoot ETL pipelines and data models for reporting needs.
Lead technical discussions with client architects and team members and guide junior team members on resolving technical challenges.
5-8 years total IT experience with at least 3 years in Data Warehouse/ETL projects.
Mandatory skills: Azure Databricks, PySpark, SQL, Python, Azure Data Factory, ETL.
Bachelor's or Master’s degree in Computer Science or equivalent experience.
Experience working with data modeling (Star and Snowflake), SQL performance tuning, and cloud platforms (AWS/Azure).
Experienced in building and orchestrating data pipelines using Azure Databricks and Airflow in Agile environments.
Comfortable handling complex data (structured, unstructured, streaming) and knowledgeable in Data Management principles and big data tools (Kafka, Hadoop, NoSQL databases).
Capable of driving technical discussions with clients and mentoring team members with strong analytical and problem-solving skills.