Job Description

Who We Are
Addepar is a global technology and data company that helps investment professionals provide the most informed, precise guidance for their clients. Hundreds of thousands of users have entrusted Addepar to empower smarter investment decisions and better advice over the last decade. With client presence in more than 45 countries, Addepar’s platform aggregates portfolio, market and client data for over $6 trillion in assets. Addepar’s open platform integrates with more than 100 software, data and services partners to deliver a complete solution for a wide range of firms and use cases. Addepar embraces a global flexible workforce model with offices in Silicon Valley, New York City, Salt Lake City, Chicago, London, Edinburgh and Pune.

The Role
We are seeking an experienced Senior Data Engineer to join the Reference Data Team, a critical component of the Addepar Platform team. The Addepar Platform is a comprehensive data fabric that provides a single source of truth for our product set, encompassing a centralized and self-describing repository, API driven data services, integration pipeline, analytics infrastructure, warehousing solutions, and operating tools.

The Reference Data Team is responsible for the acquisition, conversion, cleansing, reconciliation, modeling, tooling, and infrastructure related to the integration of market and security master data from third-party data providers. This team plays a crucial role in our core business, enabling alignment across public and alternative investment data products and empowering clients to effectively manage their investment portfolios.

As a Senior Data Engineer on the Reference Data Team, you will collaborate closely with product counterparts in an agile environment to drive business outcomes. Your responsibilities will include contributing to complex engineering projects using a modern and diverse technology stack, including PySpark, Python, AWS, Terraform, Java, Kubernetes and more.

What You’ll Do

• Partner with multi-functional teams to design, develop, and deploy scalable data solutions that meet business requirements.
• Build pipelines that support the ingestion, analysis, and enrichment of financial data by collaborating with business data analysts
• Advocate for standard methodologies, find opportunities for automation and optimizations in code and processes to increase the throughput and accuracy of data
• Develop and maintain efficient process controls and accurate metrics that improve data quality as well as increase operational efficiency
  • Working in a fast-paced, dynamic environment to deliver high-quality results and drive continuous improvement.

Who You Are

• 5+ years of professional software data engineering experience
• A computer science degree or equivalent experience
• Proficiency with at least one object oriented programming language (PySpark, Python, Java)
• Proficiency with relational databases, SQL and data pipelines
• Rapid learner with strong problem solving skills
• Knowledge of financial concepts (e.g., stocks, bonds, etc.) is helpful but not necessary
• Experience in data modelling and visualisation is a plus
• Passion for the world of FinTech and solving previously intractable problems at the heart of investment management is a plus
• Experience with any public cloud is highly desired (AWS preferred).
• Experience with data-lake or data platforms like Databricks highly preferred.