Senior Data Engineer Snowflake MySQL Python
Fidelity Investments is a privately held, Boston-headquartered financial services company providing investing, trading, retirement, wealth management, brokerage, workplace benefits, custody and clearing, and digital-asset services.
About Fidelity Investments
Fidelity serves individual investors, employers, wealth-management firms, institutions, innovators, and charitable donors through diversified financial-services businesses. Current offerings include brokerage and trading, mutual funds and exchange-traded products, retirement and workplace savings, financial planning and advice, wealth management, institutional custody and clearing, and crypto/digital-asset products.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design, implement, maintain, tune, and test data solutions, processes, platforms, and products. You will build stored procedures and ELT pipelines, analyze and improve legacy processes, model single- and multi-tenant data solutions, and use CI/CD tooling to deliver project outcomes.
Requirements
- 5+ years in technology, including 3 years developing and deploying data solutions.
- Systems analysis experience with legacy process decomposition, debugging, tuning, refactoring, and migrations.
- SQL, Python, and stored procedure knowledge.
- Proficiency in QA and testing methodologies.
- Agile framework experience.
- Extensive SQL experience.
- MySQL, SQLMI, or Snowflake knowledge preferred.
- ETL or ELT experience; Informatica experience preferred.
- SnapLogic or Azure Functions knowledge is a plus.
- Python experience building ELT pipelines.
- Jenkins, Jenkinscore, Udeploy, Git, and GitHub experience.
- Database design and data-modeling knowledge.
Responsibilities
- Design, implement, and maintain data processes, platforms, and products.
- Build, maintain, and tune stored procedures and complex SQL queries.
- Analyze, debug, tune, refactor, and migrate legacy processes.
- Build ELT pipelines with Python or other scripting languages.
- Design single- and multi-tenant data solutions using database design and data-modeling techniques.
- Apply QA and testing methodologies.
- Use CI/CD tooling to deliver data solutions.