IT Consulting

• Primary skills:Technology->Data On Cloud - Platform->Azure Data Lake (ADL) 5–9 years of overall experience in data engineering / big data development 3+ years of hands-on experience with Azure Databricks Strong expertise in PySpark / Spark SQL Experience with Microsoft Azure services, including: Azure Data Factory (ADF) Azure Data Lake Storage (ADLS) Azure SQL / Synapse (good to have) Solid understanding of data lake / lakehouse architectures Strong SQL skills for data transformation and analytics Experience with workflow orchestration and scheduling Knowledge of data warehousing and data modeling concepts Familiarity with Git and CI/CD pipelines Excellent problem-solving and communication skills
  
  

Design, develop, and optimize data pipelines using Azure Databricks (PySpark / Spark SQL) Build and manage scalable data ingestion, transformation, and processing workflows Implement ETL/ELT pipelines using Databricks, Azure Data Factory, and related tools Develop data solutions using Azure Data Lake Storage (ADLS Gen2) Optimize Spark jobs for performance, cost, and scalability Implement best practices for data modeling, partitioning, and schema management Work with structured, semi-structured, and unstructured data Collaborate with business, analytics, and downstream BI teams Ensure data quality, reliability, and monitoring of data pipelines Support CI/CD, version control, and automated deployments

Databricks Certified Data Engineer (Associate / Professional) Experience with Delta Lake Knowledge of streaming frameworks (Structured Streaming, Event Hubs) Exposure to BI tools (Power BI, Tableau) Experience working in Agile / Scrum teams Basic understanding of Python best practices and libraries

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