Data Engineer - Tier 1 Global Asset Manager

Mondrian Alpha; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Mondrian Alpha is seeking a Data Engineer in New York City to design, build, and own robust data pipelines that drive investment decisions with quality data.

This role focuses on the firm's Snowflake platform and the integration of innovative data sources, requiring a strong ownership mentality and Python engineering skills. Experience with high-stakes financial data is favored in a challenging environment.

Qualifications

• Strong hands-on Python engineering skills.
• Experience with designing and building on Snowflake.
• Solid grasp of data warehouse design principles.
• Experience with high-stakes data quality management.
• Intellectual curiosity regarding data relevance.

Responsibilities

• Design and build robust data pipelines.
• Drive the firm's Snowflake data platform.
• Collaborate to define modern data engineering.
• Develop data quality frameworks.
• Integrate new and alternative data sources.

Skills

Python engineering skills

Snowflake experience

Pipeline orchestration

Data quality management

Ownership mentality

Tools

Airflow

Prefect

Dagster

AWS

GCP

Azure

Job description

There are asset managers, and then there are institutions. This firm is the latter. With a decades-long track record of disciplined investing and a reputation that commands respect across every corner of global finance, this is an organization that has consistently attracted - and kept - some of the most thoughtful people in the business. The culture here is one of genuine intellectual engagement, where curiosity is rewarded, ideas are taken seriously regardless of where they come from, and the work has real weight behind it. This is not a place where data engineers build pipelines into a void. The work you do here flows directly into investment decisions that move markets.

The Opportunity

This is the kind of role that does not come around often. As a Data Engineer here, you will be sitting at the intersection of modern data infrastructure and one of the most data-rich environments on the planet - financial markets. The firm is investing heavily in its data platform, and this is your opportunity to be a central architect of what that looks like. You will not be inheriting a mess and asked to keep the lights on. You will be shaping how a world-class investment organization thinks about, moves, stores, and ultimately extracts value from data at scale. The canvas is wide open and the mandate is real.

What You’ll Do

• Design, build, and own robust data pipelines that ingest, transform, and deliver high-quality financial and operational data across the organization
• Be a primary driver of the firm’s Snowflake data platform - its architecture, governance, performance optimization, and long-term scalability
• Work closely with investment, research, and quantitative teams to deeply understand their data needs and build infrastructure that makes them meaningfully faster and smarter
• Develop and enforce data quality frameworks, lineage tracking, and observability tooling so the organization can trust what it’s working with
• Identify and integrate new and alternative data sources that expand the firm’s analytical edge
• Collaborate with data scientists and analysts to productionize models and analytical workflows
• Help define what modern data engineering looks like at this firm - your opinions will matter and your decisions will stick

What We’re Looking For

• Strong hands-on Python engineering skills - not scripting, but real software craftsmanship applied to data problems
• Meaningful experience designing and building on Snowflake, including data modeling, performance tuning, and working within cloud-native data architectures
• A solid grasp of pipeline orchestration, data warehouse design principles, and the tradeoffs that come with building for scale and reliability
• Experience working with messy, high-stakes data where quality and accuracy are non-negotiable
• The intellectual curiosity to understand not just how to move data, but why it matters—what question gets answered, what decision gets made better
• An ownership mentality - someone who sees gaps and fills them, asks for forgiveness rather than permission, and takes pride in what they ship
• Ability to communicate clearly with non-technical stakeholders and translate ambiguous business needs into clean technical solutions

Nice to Have

• Familiarity with financial data - market data, pricing, reference data, corporate actions, or alternative data sets
• Experience with orchestration tools such as Airflow, Prefect, or Dagster
• Exposure to dbt for transformation workflows
• Background in a financial services, investment management, or data-intensive institutional environment
• Experience with cloud platforms (AWS, GCP, or Azure) in a data engineering context

Why This Role

The data engineering market is crowded with roles that promise scale and end up being glorified ETL maintenance. This is not that. This is a seat at the table at a firm that is serious about data as a strategic asset, backed by the resources to invest in it properly and the talent density to make the work genuinely challenging. You will be surrounded by people who push you, in an environment where what you build has a direct line to how billions of dollars get invested. The problems are hard, the data is fascinating, and the upside - professionally and financially - reflects exactly that.

If you have ever wanted to do the most interesting work of your data engineering career, this is where that happens.