Data Engineer

Nearwater Capital•New York, NY

8d•Onsite

About The Position

We are building the data infrastructure for Nearwater from the ground up, and this role sits at the center of it. As our Data Engineer, you will own the pipelines, the data quality, and the systems the business depends on to operate. You will work across a diverse set of data sources and be responsible for bringing it all together in a clean, reliable, and well-governed way. This is not a maintenance role. We are in early days, with minimal legacy baggage and significant greenfield opportunity ahead. You will be laying the foundation for how this firm handles data for years to come, and you will have real ownership over how that gets built. The right person will thrive in an environment where the architecture is yours to define and the standards are yours to set.

Requirements

3+ years of experience within financial services focused on building data pipelines
Solid proficiency in SQL and Python, with comfort writing production-quality code.
Exposure to one of the following tools or equivalent is a must: Dagster, Prefect, or Airflow
Familiarity with DuckDB or genuine interest in learning it, as it is our primary analytical data store.
Exposure to portfolio and accounting systems is a strong plus.
Experience consuming streaming or API-based data; Kafka familiarity is helpful but not a requirement.
A genuine appreciation for data quality and governance, including the willingness to define standards and enforce them.
Strong business orientation with the ability to understand why the data matters, not just how to move it.
Comfort operating independently in an early-stage environment where structure is still being built.
Interest in AI-driven development workflows and curiosity about how tooling like Claude can accelerate data work.

Nice To Haves

Familiarity with React or frontend development is a nice-to-have for future dashboard and UI contributions.

Responsibilities

Build and maintain outbound data feeds to external partners.
Own and operate our Dagster-based pipeline infrastructure, building new pipelines and maintaining existing ones as the business grows.
Ingest and transform data across a wide variety of sources including Bloomberg, Kafka streams, REST API calls, FTP pulls, and Enfusion report feeds.
Take full responsibility for data quality checks at every stage of the pipeline, identifying issues proactively before they reach downstream consumers.
Maintain and enforce data governance practices, including ownership of the data dictionary and the discipline to keep it accurate and current.
Monitor pipelines against SLAs and build toward a posture of proactive detection, with the expectation that you are on top of things before problems surface.
Support financial reporting and general ledger data initiatives, working closely with the broader team to ensure the data layer serves real business needs.
Contribute to AI-assisted workflows and tooling, including Claude-based skills and automations already in active use at the firm.
Explore opportunities in dashboarding, business intelligence, and lightweight UI development as the data platform matures.