Principal Duties and Responsibilities:
- Design, build, and operationalize data engineering solutions for internal data and analytics platforms and products.
- Implement CI/CD and other automation techniques to streamline data ingestion and delivery processes.
- Develop self-service data and analytics capabilities to empower business users to navigate our data ecosystem.
- Improve data flow architecture, emphasizing data quality, maintainability, and extensibility.
- Support process improvement on the team to enable rapid development of data products.
- Implement software engineering and DataOps standards and best practices for data analytics team, including code modularization, versioning, testing, automation of CI/CD workflows, code reviews.
- Work with data/information architects to drive enterprise taxonomy and ontology development to connect disparate data across enterprise and enable 360 insights.
- Gain an understanding of core business processes and align data development with business strategy.
- Wrangle and incorporate data from disparate systems to allow data analysts and data scientists leverage to end-to-end data and information.
Education and Experience Requirements:
- Technical Requirements (understand their purpose & able to utilize them effectively)
3+ Years:
- ETL processes & strategies
- Architecture design
- Data modeling
- Data warehousing concepts
- Data transformations and standardizations
- SDLC & workflow best practices
2+ Years:
- Azure platform features
- Snowflake Data Cloud
- Dbt
- Version control & branching strategies (Github a plus)
- Proficient in languages: SQL, Python
- Data governance, security, and compliance concepts
- Data Ingestion
