Principal Data Engineer

Job Description:

Candidate must also possess:

* Demonstrated Expertise ("DE") developing high quality data solutions in a multi-developer Agile environment according to design and coding best practices; and developing Extract, Load, Transform (ELT) and Extract, Transform, Load (ETL) pipelines to migrate data to and from Snowflake data store, using DbT, Python, and SQLMesh.

* DE assembling large, complex data sets that meet functional and non-functional business requirements; designing and implementing internal process improvements -- automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability, using Jira, Confluence, Tableau, and Actimize.

* DE designing, implementing, and maintaining scalable ETL/ELT pipelines, using tools (DbT and Snowflake); automating deployments and testing workflows, using Jenkins and Git Hub; contributing to codebases using Git, conducting code reviews, and collaborating, using Git Hub; writing unit and integration tests for data pipelines, using PyTest and DbT frameworks; and creating and maintaining technical documentation, runbooks, and onboarding guides.

* DE manipulating, processing, and extracting value from large, disparate datasets, using Alteryx, Snowflake, DbT, SQLMesh, and Python; working in financial crime typologies, AML/BSA regulations, or fraud detection methodologies.

#PE1 M2

#LI-DNI

Certifications:

Category:

Information Technology

Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.