Boston, MA, United States
13 hours ago
Lead Data Engineer

Join Us at 55ip & Help the Wealth Management Industry Move Forward

Working at 55ip, a separately branded subsidiary of J.P. Morgan, means standing at the intersection of finance and technology—and at the cutting-edge of wealth and asset management. We’ve been making rapid progress on our mission: to break down barriers to financial progress for financial advisors and their clients. Our Boston-, New York-, and Mumbai-based teams have built and brought to market a tax-smart investment strategy engine, portfolio trading and rebalancing, and advisor transition services, all delivered through an intuitive experience and intelligent automation. Driven by strategic partnerships with world-class wealth and asset management firms, we’ve experienced breakthrough growth over the last two years. Today, over 400 financial advisor firms have trusted over $100 billion in assets under supervision with 55ip.

 

As 55ip continues its rapid growth trajectory, we are on the path to managing over $1 trillion in assets under supervision (AUS) by 2030. This scale brings significant challenges and opportunities, including supporting exponential increases in accounts, net flows, revenue, and pre-tax income. Our technology platform must evolve to handle this growth, ensuring robust performance, reliability, and automation for tax-smart investing portfolios across diverse product mixes and client segments.

 

Lead Data Engineer 

55ip’s Quantitative Research & Development team is looking for a lead data engineer to take part in building its research data platform.  The ideal candidate has a background in implementing effective large-scale data solutions in a cloud-based environment.  The candidate will be motivated, a problem solver, a team player, and an effective engineer, looking to make a significant impact.

 

Responsibilities

Build high-performance cloud-based data solutions to support quantitative research capabilities: back testing, simulations, machine learning, and other advanced analytics & algorithms Implement, schedule, and oversee ETL, ELT, and monitoring processes Oversee the loading of data from vendor and internal data sources Implement and support automation solutions to improve platform scalability Monitor the system performance by performing regular tests, troubleshooting, and integrating new features Provide L2 support for data systems to stakeholder teams Collaborate with technical teams to design and implement data solutions Recommend solutions to improve new and existing data systems


 

Requirements

Bachelor's degree in information systems, information technology, computer science, or similar. Expertise in Structured Query Language (SQL); experience with PostgreSQL specifically is a plus Expertise in Python, Pandas/Polars, and Numpy Clear understanding of OOP and software design constructs within a Python context Expertise with AWS Cloud services/technologies, such as RDS, S3, Lambda, Secrets Manager Expertise in all aspects of software development lifecycle, especially Agile Scrum Strong Experience implementing and monitoring ETL processes Strong Experience with database technologies, architecture, performance tuning, and scaling Strong Experience in database design and modeling Experience with Airflow or similar orchestration tools Experience working with and CI/CD tools for application and database development Excellent communication (written and oral) and presentation skills Ability to work with quant researchers & developers to understand requirements Strong attention to detail, pride in delivering high quality work and willingness to learn Agility: Able to shift gears and react quickly to timely requests

 

Preferred Qualifications

Experience working with Data Lakes (Iceberg/DeltaTable) Experience working with DuckDB, Spark, and EMR  Experience supporting development of AI/ML models Exposure to financial capital markets data and trading applications, working with investment data AWS certifications are a plus Experience with project workflow tools such as Jira in an Agile-Scrum environment Knowledge of Linux

 

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