Data Engineer

Solomon Page; New York (NY); Hybrid; USD 175,000 - 240,000; Full time

Job summary

Solomon Page partners with a highly successful investment management firm to hire a Senior Data Engineer who will transform and modernize its enterprise data platform. You will own data architecture, cloud migration, market data engineering, analytics platforms, and API infrastructure in a lean, high‑performing technology and data team.

Based in New York City with a hybrid schedule (4 days in the office and occasional WFH), the role offers 175–240k base salary plus bonus and benefits.

Qualifications

• 5+ years of data engineering in financial services.
• Experience with hedge funds or asset management environments.
• Strong SQL skills and SQL Server expertise.

Responsibilities

• Lead cloud migration and modernize the firm's data platform.
• Design and maintain ELT pipelines using Python/SQL, Snowflake, dbt.
• Build market data pipelines across Fixed Income, FX, rates, commodities.
• Develop scalable data models and enterprise warehouse solutions.
• Implement data governance, quality controls, and lineage.
• Develop APIs and analytics services.

Skills

SQL development

Microsoft SQL Server

Snowflake

dbt

APIs & data integration

Tools

Power BI

Tableau

Azure Data Factory

Databricks

Synapse

Job description

We are partnering with a highly successful and growing investment management firm seeking a Senior Data Engineer to help transform and modernize its enterprise data platform. This is a unique opportunity to join a lean, high-performing technology and data team where your work will have immediate visibility and measurable impact across the organization. Unlike large financial institutions where responsibilities can be narrowly defined, this role offers broad ownership across data architecture, cloud migration, market data engineering, analytics platforms, and API infrastructure. The firm invests across global markets with a particular focus on Fixed Income, Credit, FX, Interest Rates, Commodities, and derivative products. Data is central to the investment process, and this position will play a critical role in building the next generation of data infrastructure that supports portfolio managers, traders, researchers, and business stakeholders.

• The role is based in New York City and is a hybrid work environment with 4 days a week in the office with additional flexibility to work from home two weeks a year. Compensation is based on expereince but the range is 175-240k base plus bonus and benefits. The company can not sponsor at this time and will only consider US Citizens or Green Card holders.

Responsibilities:

Data Platform Modernization

• Lead the evolution of the firm's data platform from legacy on-premise environments into a modern cloud-based architecture.
• Design, build, and maintain scalable ELT pipelines using Python, SQL Server, Snowflake, and dbt.
• Integrate data from vendor feeds, APIs, market data providers, and internal systems.
• Develop robust frameworks for data ingestion, transformation, and storage.

Market Data Engineering

• Build and optimize pipelines supporting complex market data analytics.
• Work with Fixed Income, Credit, FX, Rates, Commodities, and derivatives datasets.
• Support yield curve construction, pricing analytics, risk analytics, P&L attribution, and reference data management.
• Partner with investment professionals to deliver reliable, high-quality datasets.

Cloud & Data Warehouse Architecture

• Help drive migration initiatives from SQL Server and legacy environments into Snowflake.
• Design scalable data models and enterprise warehouse solutions.
• Implement best practices around performance tuning, governance, lineage, and data quality.

Analytics & API Development

• Enhance Python-based data services and APIs that power investment workflows.
• Optimize reporting and analytics environments through indexing, clustering, caching, and query tuning.
• Support business intelligence and self-service analytics initiatives.

Data Governance & Quality

• Build automated monitoring and validation frameworks.
• Develop controls for stale data detection, schema drift, duplicate records, and anomaly identification.
• Maintain data cataloging, ownership, lineage, and quality standards across the platform.

Required Qualifications:

Required Experience

• 5+ years of experience in Data Engineering, Analytics Engineering, or Data Platform Engineering.
• Prior experience within a:
• Hedge Fund
• Asset Management Firm
• Investment Management Firm
• Private Equity Firm
• Alternative Asset Manager
• Capital Markets or Trading Environment

Technical Skills

• Expert-level SQL development and performance tuning.
• Strong experience with Microsoft SQL Server.
• Hands-on experience with Snowflake.
• Strong experience building and maintaining dbt frameworks.
• Experience working with APIs and data integration platforms.

Capital Markets Experience

Candidates must have strong exposure to financial market data and investment workflows, ideally including:

• Fixed Income
• Credit Products
• Interest Rate Products
• Commodities
• Yield Curves
• Security Master Data
• Market Data Platforms
• Bloomberg, LSEG/Refinitiv, FactSet, ICE, or similar data providers

Preferred Qualifications

• Experience with Azure, Azure Data Factory, Databricks, or Synapse.
• Experience migrating data platforms from SQL Server to modern cloud environments.
• Exposure to high-performance trading systems or electronic trading platforms.
• Experience with Power BI, Tableau, or enterprise reporting environments.
• Familiarity with event-driven architectures, CDC, streaming technologies, or real-time market data.
• Experience building semantic layers and AI-ready data platforms.