- Developing Modern Data Warehouse solutions using Databricks and Azure Stack
- Ability to provide solutions that are forwardthinking in data engineering and analytics space
- Collaborate with DW/BI leads to understand new ETL pipeline development requirements.
- Triage issues to find gaps in existing pipelines and fix the issues
- Work with business to understand the need in reporting layer and develop data model to fulfill reporting needs
- Help joiner team members to resolve issues and technical challenges.
- Drive technical discussion with client architect and team members
- Orchestrate the data pipelines in scheduler via Airflow Skills
- Must have a total 4+ yrs. of IT experience experience in Data warehouse/ETL projects.
- Deep understanding of Star and Snowflake dimensional modeling.
- Strong knowledge of Data Management principles
- Good understanding of Databricks Data & AI platform ans ADB
- Should have handson experience in SQL, Python and Spark (PySpark)
- Candidate must have experience in Azure stack
- Desirable to have ETL with batch and streaming (Kinesis).
- Experience in building ETL / data warehouse transformation processes
- Experience working with structured and unstructured data including imaging & geospatial data.
- Experience working in a Dev/Ops environment with tools such as Terraform, CircleCI, GIT.
- Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning and troubleshoot
- Databricks Certified Data Engineer Associate/Professional Certification (Desirable).
- Comfortable working in a dynamic, fastpaced, innovative environment with several ongoing concurrent projects
- Should have experience working in Agile methodology
- Strong verbal and written communication skills.
- Strong analytical and problemsolving skills with a high attention to detail.
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Description
Primary Roles and Responsibilities :
/ PySpark / Spark with Azure/Databricks/SQL/Python/Azure Datafactory
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