Databricks & Spark: Hands-on experience with Databricks, Apache Spark, and PySpark for big data processing.
Cloud Platforms: Proficiency in Azure (preferred), AWS, or GCP for data engineering workflows • SQL & Data Modeling: Strong knowledge of SQL, schema design, and dimensional data modeling.
ETL/ELT Tools: Experience with tools like Azure Data Factory, Informatica, or Talend.
Data Warehousing: Familiarity with technologies such as Azure Synapse, Snowflake, or BigQuery.
Robust problem-solving and debugging skills.
Excellent communication and teamwork abilities.
Ability to work in a quick-paced, agile environment.
Good-to-Have • Knowledge of Event Hub, IoT Hub, and streaming analytics. • Exposure to Power BI, Azure DevOps, and CI/CD pipelines. • Understanding of machine learning libraries (MLlib) and predictive analytics.