Principal Data Engineer

Fidelity Investments • Merrimack, NH

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About The Position

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 GitHub; contributing to codebases using Git, conducting code reviews, and collaborating, using GitHub; 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. #PE1M2 #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. At Fidelity, we are passionate about making our financial expertise broadly accessible and effective in helping people live the lives they want! We are a privately held company that places a high degree of value in creating and nurturing a work environment that attracts the best talent and reflects our commitment to our associates. We are proud of our diverse and inclusive workplace where we respect and value our associates for their unique perspectives and experiences. For information about working at Fidelity, visit FidelityCareers.com. Fidelity Investments is an equal opportunity employer. Fidelity will reasonably accommodate applicants with disabilities who need adjustments to participate in the application or interview process. To initiate a request for an accommodation please contact the following: For roles based in the US: Contact the HR Leave of Absence/Accommodation Team by sending an email to [email protected], or by calling 800-835-5099, prompt 2, option 2 For roles based in Ireland: Contact [email protected] For roles based in Germany: Contact [email protected] Fidelity Privacy Policy

Requirements

• Demonstrated Expertise (“DE”) developing high quality data solutions in a multi-developer Agile environment according to design and coding best practices
• 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
• 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
• Designing, implementing, and maintaining scalable ETL/ELT pipelines, using tools (DbT and Snowflake)
• Automating deployments and testing workflows, using Jenkins and GitHub
• Contributing to codebases using Git, conducting code reviews, and collaborating, using GitHub
• Writing unit and integration tests for data pipelines, using PyTest and DbT frameworks
• Creating and maintaining technical documentation, runbooks, and onboarding guides
• 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

Responsibilities

• Developing high quality data solutions in a multi-developer Agile environment according to design and coding best practices
• 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
• 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
• Designing, implementing, and maintaining scalable ETL/ELT pipelines, using tools (DbT and Snowflake)
• Automating deployments and testing workflows, using Jenkins and GitHub
• Contributing to codebases using Git, conducting code reviews, and collaborating, using GitHub
• Writing unit and integration tests for data pipelines, using PyTest and DbT frameworks
• Creating and maintaining technical documentation, runbooks, and onboarding guides
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed