Data Engineer

Role & responsibilities

• Solid database understanding of SQL experience and data modelling.
• Understanding of DWH architecture (EDW / DM concepts, Star and snowflake schema)
• Strong Experience working on designing and building data pipelines on Azure Cloud stack
• Strong experience on one of the Cloud Services
• Azure: Data Fabric, Data Explorer, Data factory, Data Bricks, Synapse and Azure SQL Datawarehouse
• AWS: Glue, Athena, S3, Redshift, RDS
• GCP: Big Query, Big Table, Data Proc, Data Prep
• Expert knowledge and experience working with any one of the ETL tools/Technologies: Informatica, SSIS, Talend etc.,
• Knowledge and experience on DevOps and CI/CD Pipelines
• Expertise with on premise database environments such as Oracle, SQL Server, MySQL and/or Postgres.
• Experience or Knowledge on Cloud Datawarehouses: SNOWFLAKE
• Experience with data visualization utilizing Power BI or SSRS or Tableau
• Hands-on Experience building or working with Medallion, Data Lake and Lakehouse Architectures
• Demonstrated problem solving with experience providing business insights from large data sets.
• Interpret data, analyze results using statistical techniques and provide ongoing reports.
• Excellent oral and written communication skills, and ability to provide strategic direction to both technical and business organizations.
• Ability to articulate complex data solutions concisely and with clarity at senior management level.
• Experience implementing, managing, supporting data warehouse projects or applications.
• Experience in leading and delivering full-cycle implementation projects related to Business Intelligence.
• Strong attention to detail and accuracy with ability to meet deadlines with short lead times.
• Knowledge on Application development, APIs, Microservices, Integration components