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Senior Data EngineerGen II Fund Services • New York, New York, United States
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Senior Data Engineer

Gen II Fund Services
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

Senior Data Engineer – Technology With 13 offices and more than 1,900 employees in the U.S., Canada, the UK, and Europe, Gen II is a leading fund administration provider focused entirely on serving private capital asset managers and investors with best‑in‑class people, process, and technology. We’re looking for do‑ers, problem‑solvers, and entrepreneurs who want to make an impact, grow with us, and create a community where everyone thrives.
What’s the role? Gen II is building out its Data & Integration Platform (DIP) – the central data backbone that powers data integration, analytics, reporting, and AI capabilities across our fund administration technology estate. At the heart of DIP is a Snowflake‑based medallion data architecture – Bronze, Silver, and Gold – fed by integrations across 40+ systems and consumed by business intelligence, client‑facing products, and AI‑driven services.
We are looking for a Senior Data Engineer to join the DIP team and take direct ownership of data layer delivery – building and maintaining the Bronze, Silver, and Gold layers that turn raw system data into trusted, analytics‑ready assets. The data engineering function is AI‑assisted: AI tooling (LLMs, codegen, Claude) is a natural part of how you work, whether generating transformation logic, scaffolding Streamlit applications, or accelerating documentation.
You will come in, get up to speed quickly, and drive data workstreams forward with minimal oversight. You will report to and work closely with the Associate Director of Data Engineering to establish and maintain data platform standards and patterns.
What you’ll be doing Snowflake Data Layer Build
Building and maintaining Bronze → Gold layers within Snowflake, effectively moving data throughout Snowflake for reporting, analytics and egress to downstream systems.
Designing and implementing Snowflake data models aligned to the Gen II canonical domain model – fund structures, investors, GL, NAV, compliance.
Developing and maintaining Snowflake Streams, Tasks, and Stored Procedures for pipeline orchestration and incremental processing.
Owning data quality – implementing validation, monitoring, and alerting within the pipeline to ensure Gold layer data is trustworthy.
Working with Fivetran‑synced data from source systems and Snowflake Secure Data Shares, building clean ingestion patterns at the Bronze/Silver boundary.
AI‑Assisted Development
Using AI tooling across all data engineering work – generating transformation SQL, scaffolding Python scripts, producing test cases, and automating documentation; AI assistance is the default mode of working.
Contributing to a data factory approach – reusable, metadata‑driven patterns for transformation, testing, and deployment that can be applied consistently across data streams.
Building Streamlit applications in Snowflake for internal operational tooling – data review queues, reconciliation dashboards, client provisioning workflows, and similar.
Writing Python scripts and utilities to support data processing, validation, and operational tasks within the DIP ecosystem.
Contributing to pytest‑based test suites for data pipeline validation, aligned to DIP QA standards.
Analytics & BI Enablement
Structuring Gold layer outputs to serve downstream consumers – Power BI, Qlik, and client‑facing analytics products.
Collaborating with BI specialists to ensure data models support reporting requirements without duplication or technical debt.
Supporting the establishment of master data management and golden record patterns across key fund administration entities.
Delivery & Collaboration
Taking data workstreams from requirement to production with minimal hand‑holding.
Working closely with the Associate Director of Data Engineering, integration engineers, BAs, and QA – raising blockers early and documenting decisions clearly.
Collaborating with integration engineers to ensure data lands cleanly at the Bronze/Silver boundary and conforms to agreed schemas.
Contributing to data governance practices – lineage, catalogue, access control, and data quality standards.
The ideal background for this role
5+ years
of hands‑on data engineering experience – evidenced in role history, not just a skills list.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
Deep practical Snowflake expertise – data modelling, SQL optimisation, Streams/Tasks/Stored Procedures, Secure Data Shares. SnowPro certification a plus.
Strong Python development – data processing scripts, utilities, and Streamlit applications.
Experience building Bronze/Silver/Gold medallion architectures or equivalent layered data warehouse patterns.
Hands‑on experience with Fivetran or equivalent ELT tooling for source system ingestion desired.
Active use of AI‑assisted development in data engineering delivery – transformation generation, test scaffolding, documentation automation.
Experience with BI tooling – Power BI and/or Qlik – and structuring data models to serve reporting consumers effectively.
Ability to own workstreams independently and drive delivery without close management.
Experience with data governance, data quality frameworks, and master data management – desirable.
Exposure to fund administration, private capital, or broader financial services environments – desirable.
Familiarity with AI/ML concepts and their application to financial services data – desirable.
Strong communication skills with the ability to collaborate across technical and business teams.
The salary range for this position is $140,000 – $170,000, in addition to a discretionary bonus and comprehensive benefits package. Please note that the actual salary offered within that range will depend on the candidate’s experience level.
Work Arrangement All applicants applying to Gen II Fund Services, LLC must be legally authorized to work in the United States. This role follows a flexible hybrid schedule, with the resource expected in the office 1–4 days per week on a need basis.
Candidate Privacy & EEO Statement For further information, please review the Know Your Rights notice from the Department of Labor.
Equal Opportunity Employer / Protected Veterans / Individuals with Disabilities. This employer is required to notify all applicants of their rights pursuant to federal employment laws.
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  • New York, New York, United States

Sprachkenntnisse

  • English
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