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.

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.

• 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

• Bachelor's degree in information systems, information technology, computer science, or similar.
• Expertise in Structured Query Language (SQL); experience with Postgre
  
  SQL 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.

• Experience working with Data Lakes (Iceberg/Delta Table).
• 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.