Position Description:
Develops data pipelines that support next generation surveillance solutions on a wide range of anti-money laundering (AML) typologies, primarily supporting the team’s work in the money movement, trading, and cryptocurrency space. Collaborates across teams to understand the various regulatory (FINRA, OCC, and FinCEN) red flags and risks, and acquires data, performs data analysis, and builds new features to improve detection. Works with machine learning (ML) models, rewrites legacy models, and supports the data preparation for reporting efforts. Simplifies infrastructure and production support complexity. Develops model performance metrics and makes model adjustments accordingly to ensure models are performing optimally. Develops features using various technologies -- Data Build Tool (DBT), Snowflake, SQLMesh, and Python. Assists in the architectural design and implementation of the transaction monitoring platform that enables and scales the newest business initiatives, including digital assets and other emerging technologies. Creates robust testing scenarios, including unit testing, regression testing, and model performance.
Primary Responsibilities:
- Provides technical leadership, mentoring, and training to other team members through code reviews, collaboration, and educational presentations.
- Explores new technologies and emerging trends and determines their applicability to use cases and orchestrates the adoption of technologies and trends.
- Develops complex or multiple data engineering solutions and conducts studies of alternatives to translate divisional initiatives into business solutions.
- Analyzes and recommends changes in project development policies, procedures, standards, and strategies to development experts and management.
- Participates in architecture design teams.
- Defines and implements application-level architecture.
- Develops applications, components, and subsystems to support division-wide complex projects.
- Recommends development testing tools and methodologies.
- Establishes full project life cycle plans for complex projects across multiple platforms.
- Advises on risk assessment and risk management strategies for projects.
- Plans and coordinates project schedules and assignments for multiple projects.
- Provides technology solutions to daily issues and estimates technical evaluation requirements for technology initiatives.
- Mentors junior team members.
Education and Experience:
Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Principal Data Engineer (or closely related occupation) developing data pipelines using Continuous Integration and Continuous Delivery (CI/CD) and deploying code and services to cloud-based data platforms -- DbT and Snowflake.
Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and three (3) year of experience as a Principal Data Engineer (or closely related occupation) developing data pipelines using Continuous Integration and Continuous Delivery (CI/CD) and deploying code and services to cloud-based data platforms -- DbT and Snowflake.
Skills and Knowledge:
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.
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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.
Skills Required
- Develop high quality data solutions in a multi-developer Agile environment following design and coding best practices
- Develop ELT/ETL pipelines to migrate data to and from Snowflake using DbT, Python, and SQLMesh
- Assemble large, complex data sets that meet functional and non-functional business requirements
- Design and implement internal process improvements: automate manual processes, optimize data delivery, redesign infrastructure for scalability using Jira, Confluence, Tableau, and Actimize
- Design, implement, and maintain scalable ETL/ELT pipelines using DbT and Snowflake
- Automate deployments and testing workflows using Jenkins and GitHub; contribute to codebases using Git and perform code reviews
- Write unit and integration tests for data pipelines using PyTest and DbT frameworks
- Create and maintain technical documentation, runbooks, and onboarding guides
- Manipulate, process, and extract value from large, disparate datasets using Alteryx, Snowflake, DbT, SQLMesh, and Python
- Experience working in financial crime typologies, AML/BSA regulations, or fraud detection methodologies
Fidelity Investments Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fidelity Investments and has not been reviewed or approved by Fidelity Investments.
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Strong & Reliable Incentives — Bonuses, commissions, and profit-sharing are presented as generous and meaningful components of total compensation, with certain roles achieving high total earnings through multiple pay streams. Variable pay is consistently framed as a positive contributor beyond base salary.
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Retirement Support — A 401(k) match up to 7% alongside additional profit-sharing up to 10% materially enhances long-term compensation. These retirement features are highlighted as standout strengths of the overall package.
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Parental & Family Support — Generous paid parental leave (16 weeks maternity, 12 weeks parental), backup dependent care, and adoption assistance provide robust family support. Hybrid work and caregiving resources further ease family responsibilities.
Fidelity Investments Insights
What We Do
At Fidelity, our goal is to make financial expertise broadly accessible and effective in helping people live the lives they want. We do this by focusing on a diverse set of customers: - from 23 million people investing their life savings, to 20,000 businesses managing their employee benefits to 10,000 advisors needing innovative technology to invest their clients’ money. We offer investment management, retirement planning, portfolio guidance, brokerage, and many other financial products. Privately held for nearly 70 years, we’ve always believed by providing investors with access to the information and expertise, we can help them achieve better results. That’s been our approach- innovative yet personal, compassionate yet responsible, grounded by a tireless work ethic—it is the heart of the Fidelity way.
