Work from Office
- To collaborate with various teams/regions in driving facilitating data design, identifying architectural risks and key areas of improvement in data landscape, and developing and refining data models and architecture frameworks
- Technical experience and knowledge in Cloud Data Warehousing, data migration and data transformation
- Develop and test ETL components to high standards of data quality and performance as a hands-on development lead
- Familiarity with Data Lakes, Data Warehouses, MDM, BI, Dashboards, AI, ML
- Design data architecture patterns and ecosystems including data stores (operational systems, data lakes, data warehouses, data marts), ingress patterns (API, streaming, ETL/ELT), and egress patterns (analytics/decision tools, BI tools). Lead, consult or oversee multiple architectural engagements
- Oversee and contribute to the creation and maintenance of relevant data artifacts (data lineages, source to target mappings, high level designs, interface agreements, etc.) in compliance with enterprise level architecture standards
- Experience in leading and delivering data centric projects with concentration on Data Quality and adherence to data standards and best practices.
- Experience in data modeling, metadata support, development and testing for enterprise wide data solutions
- Azure cloud experience is a must have with familiarity of the services: Azure Databricks, Azure Datafactory, Azure Datalake, Spark SQL, PySpark, Airflow, SQL server and Informatica MDM.
- Additional exposure to GCP and AWS is good to have.
Key Skill: Azure Databricks, ADF, ETL, Pipeline Dev, SQL, DWH, ADLS.