Principal Data Engineer - Financial Crimes Compliance Technology

Job Description:

The Role

Principal Data Engineer – Financial Crimes Compliance Technology

Fidelity is seeking to hire a seasoned Principal Data Engineer to join our Financial Crimes Models & Analytics team to assist with the ongoing transformation of the firm’s Financial Crimes Compliance program, especially in the cryptocurrency space. If you are enthusiastic about data engineering, data science, and technology to help fight financial crime, then this is an excellent opportunity for you! As Principal Data Engineer, you will be:

• Responsible for owning the development of data pipelines that support next generation surveillance solutions on a wide range of anti-money laundering typologies, primarily supporting the team’s work in the digital assets space.
• Working with business partners across various domains to acquire data, performing data analysis, and building new features to improve our detection.
• Working with machine learning models, rewriting legacy models, and supporting the data preparation for our reporting efforts. You will also strive to simplify our infrastructure and production support complexity.
• Developing model performance metrics and making model adjustments accordingly to ensure models are performing optimally. 
• Protecting Fidelity’s customers and brand by identifying bad actors or victims on the platform.
• Bringing on the latest implementations of emerging technologies into Fidelity’s Financial Crimes Detection Program.
• Detecting suspicious activity occurring on Fidelity’s platform 
• Supporting Fidelity’s new business initiatives, e.g., Fidelity Digital Assets. 
• Helping to develop and advance your teammates by sharing your experience, expertise, and perspective. 
• Collaborating across Financial Crimes Compliance to understand the various red flags and risks that our models attempt to detect, especially in the cryptocurrency space.
• Developing features using various technologies, including DBT and Snowflake, as well as Python.
• Assisting in the architectural design and implementation of the transaction monitoring platform that enables and scales Fidelity’s newest business initiatives, including digital assets and other emerging technologies.
• Lead the transformation of experimental AI/machine learning algorithms into scalable, robust production-ready processes. 
• Create robust testing scenarios, including unit testing, regression testing, and model performance. 
• Provide technical leadership, mentoring and training to other team members through code reviews, collaboration, and educational presentations. 
• Explore modern technologies, emerging trends and determine their applicability to the team’s use cases; orchestrate the adoption of such technologies and trends where appropriate. 

The Expertise and Skills You Bring  

• Bachelor's degree in computer science or equivalent technical expertise 
• Possess minimum of 6+ years of software or data engineering experience, including prior experience leading and delivering complex data engineering projects. 
• Possess excellent proficiency in Python or PySpark, required.
• Possess big data experience with Snowflake or Hadoop, required.
• Experience working with DBT (data build tool) or Databricks is a plus.
• Experienced and proficient in designing and developing data pipelines, scalable architectures, and data modeling. 
• Experience in the software development cycle from design to implementation to testing, CI/CD, version control management/git, documentation, etc. 
• Excellent proficiency in querying relational databases, e.g., Oracle, Snowflake, and non-relational databases, e.g., MongoDB 
• A strong understanding of digital assets and blockchain technologies; Prior experience in the cryptocurrency space is a plus. 
• Experience developing pipelines that support AI/Machine Learning processes nice to have,
• Familiarity with a distributed system such as Apache Iceberg or Snowflake 
• Familiarity with ML algorithms such as decision trees, autoencoders/neural networks, linear/logistic regression, clustering, etc. 
• Experience in the Financial Services industry, Financial Crimes space particularly desirable.
• You are thoughtful in the approach and design of technology solutions. 
• You are committed to working with our business partners, systems analysts, data engineers, and data scientists to build the best system possible. 
• You adhere to and enforce engineering best-practices (Git, documentation, test automation).
• Love of technology — following trends and trying them in small scale to see how they work. 
• Have an eye for detail and are committed to quality and ambit