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Strong employer brand, metro location, mid-level generalist title and experience, and broad Azure skill demand.
Azure Databricks and Synapse specialization increases domain bias, yet core data engineering skills remain transferable across industries.
Explicit 4–6 years requirement plus mandatory Azure Databricks/ADF and ETL skills enforces strict filtering.
Develop and manage Azure Data Factory pipelines for ETL processing including copy activity and custom Azure development.
Handle data engineering tasks using Azure Databricks, ADF, Delta Lake, and related Azure data services to support data lake, data warehouse, and analytics requirements.
Translate business requirements into functional specifications for data reporting applications.
4-6 years of professional experience in data engineering or relevant field.
Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Delta Lake, Azure Data Lake, Azure Synapse Analytics, data warehouse technologies, SQL, Python, and Cosmos DB.
Proficient in building and managing ETL workflows using Azure Data Factory pipelines.
Knowledge of semi-structured data and streaming data processing.
Experienced in end-to-end Azure cloud data engineering environments with strong ETL and pipeline automation skills.
Skilled in working with various Azure data services including Databricks, Synapse Analytics, Data Lake, and SQL Data Warehouse.
Capable of aligning technical data solutions with business requirements for reporting and analytics.