Azure Data Engineer

Role: Azure Databricks Data Engineer

Design/Development : You will design and support the business s database and table schemas for new and existing data sources for the Lakehouse. Create and support the ETL in order to facilitate the movement of data into the Lakehouse.
Through your work you will ensure
The data platform is scalable for large amounts of data ingestion and processing without service degradation.
Processes are built for monitoring and optimizing performance
Implement Chaos Engineering practices and measures that allow the end-to-end infrastructure to function as expected, even if individual components fail
Collaboration : You will be collaborative - working closely with Product Owners, application engineers, and other data consumers within the business in an attempt to gather and deliver high quality data for business-cases. Work closely with other disciplines/departments and teams across the business in coming up with simple, functional, and elegant solutions that balance data needs across the business
Analytics : You will play an analytical role in quickly and thoroughly analyzing business requirements and subsequently translating the emanating results into good technical data designs. Document the data solutions, develop, and maintain technical specification documentation for all reports and processes.

Skills you MUST have:
6+ years proven ability of professional Data Development experience
3+ years proven ability of developing with Azure Databricks or Hadoop/HDFS
3+ years of experience with PySpark/Spark
3+ years of experience with SQL
3+ years of experience developing with Python
Full understanding of ETL concepts and Data Warehousing concepts
Data modeling and query optimization skills, implementation experience of Data Vault, Star Schema and Medallion architecture
Experience with CI/CD
Experience with version control software
Strong understanding of Agile Principles (Scrum)
Experience with Azure
Experience with Databricks Delta Tables, Delta Lake, Delta Live Tables

Bonus Points For Experience In The Following
Proficient with Relational Data Modeling
Experience with Python Library Development
Experience with Structured Streaming (Spark or otherwise)
Experience with Kafka and/or Azure Event Hub
Experience with GitHub SaaS / GitHub Actions
Experience with Snowflake/ Exposure to BI Tooling (Tableau, Power BI, Cognos, etc.)