Data Engineer

Key Responsibilities

Design and build scalable data pipelines and data lake/warehouse solutions on Azure and Databricks.
Work extensively with SQL, schema design, and dimensional data modeling.
Develop and maintain ETL/ELT processes using tools like ADF, Talend, Informatica, etc.
Leverage Azure Synapse, Azure SQL, Snowflake, Redshift, or BigQuery to manage and optimize data storage and retrieval.
Utilize Spark, PySpark, and Spark SQL for big data processing.
Collaborate cross-functionally to gather requirements, design solutions, and implement best practices in data engineering.

Required Qualifications

Minimum 5 years of experience in data engineering, data warehousing, or data lake technologies.
Strong experience on Azure cloud platform (preferred over others).
Proven expertise in SQL, data modeling, and data warehouse architecture.
Hands-on with Databricks, Spark, and proficient programming in PySpark/Spark SQL.
Experience with ETL/ELT tools such as Azure Data Factory (ADF), Talend, or Informatica.
Strong communication skills and the ability to thrive in a fast-paced, dynamic environment.
Self-motivated, independent learner with a proactive mindset.

Nice-to-Have Skills

Knowledge of Azure Event Hub, IoT Hub, Stream Analytics, Cosmos DB, and Azure Analysis Services.
Familiarity with SAP ECC, S/4HANA, or HANA data sources.
Intermediate skills in Power BI, Azure DevOps, CI/CD pipelines, and cloud migration strategies.