Data & Infrastructure Engineer

Data & Infrastructure Engineer

• Merchant Wealth Partners (MWP) is a rapidly growing, New York-based company that acquires equity interests in and partners with high-quality, growing wealth management companies (“Hub Partners”).
• MWP was launched in 2017 by executives with deep domain expertise in wealth management and financial services stemming from Apollo, Goldman Sachs, United Capital, Skybridge Capital, Focus Financial, Dynasty Financial Partners and Purshe Kaplan Sterling Investments. The business has scaled to more than 150 hub partners and more than $400 billion in assets across the ecosystem. Today, its RIA partners span 48 states and 5 countries. MWP has built a platform, brand and ecosystem to facilitate growth, improve operating efficiency and maximize value for its partners throughout their lifecycle.

• Why Join Merchant
• Merchant is building a robust data capability that is driving consolidation and automation across finance, investment, pipeline and hub intelligence workflows. These automated data integrations are becoming the backbone for how Merchant moves data, measures performance and makes decisions.
• You will sit at the point where raw data becomes trusted infrastructure. One day you may build a recurring API or file-based ingestion process. The next, you may trace a financial reporting break to a source field, productionize a SQL transformation, tighten an access-control pattern or ship a dataset that senior leaders use immediately.
• Your work will power executive decision-making, finance and control reporting, portfolio intelligence, hub integration and practical AI capabilities across hundreds of billions in assets. We value ownership, precision, curiosity, intellectual honesty and disciplined execution.
• MWP is seeking a hands-on engineer to build, operate and improve the data pipelines, cloud services and production controls behind Merchant’s enterprise data platform. This role blends data engineering, analytics engineering and practical infrastructure work for someone who can move from source-system discovery to runnable code, validation, documentation and reliable production support.

• Key Responsibilities
• Build and operate production data pipelines into Snowflake from APIs, SFTP, cloud storage, vendor exports, databases and structured or semi-structured files.
• Write, test and maintain advanced SQL, Python and dbt transformations that convert raw source data into trusted, reusable enterprise data products.
• Implement canonical data models and business hierarchies across firms, practices, advisors, households, accounts, investments and financial reporting domains.
• Reconcile source-system output to finance and operational reporting. Trace discrepancies to the field, transformation or business rule and drive them through resolution.
• Build and maintain semantic models, datasets and Sigma reporting that support finance, liquidity, pipeline, portfolio and hub-performance workflows.
• Own the practical infrastructure around data movement, including authentication, service accounts, credentials, secrets, schedules, permissions, monitoring, retry logic and failure handling.
• Embed automated testing, observability, lineage, data-quality controls and release discipline into production workflows. If a pipeline fails or a number changes, we should know why.
• Translate ambiguous business requirements into deterministic technical logic by working directly with Finance, Operations, Ecosystem, Legal, outside vendors and subject-matter experts.
• Create clear source-to-target mappings, field-level definitions, runbooks and technical documentation that another engineer can actually use.
• Operate what you build. Support hub-data integrations, source-grounded automation and AI-enabled workflows, triage production issues and improve the system so the same failure does not recur.

Qualifications

• Hands-on experience in data engineering, analytics engineering, cloud infrastructure or a closely related role. We care more about what you have shipped than the labels on your prior roles.
• Advanced SQL proficiency is absolutely required, with strong Python proficiency for data processing, automation, integration and validation.
• Production experience with Snowflake, dbt, Fivetran, Sigma or comparable cloud data, transformation, ingestion and analytics platforms.
• Experience integrating systems through REST APIs, OData, SFTP, CSV or JSON files, cloud object storage and scheduled vendor extracts.
• Working knowledge of infrastructure fundamentals including identity and access management, authentication, secrets handling, role-based permissions, orchestration, monitoring and production support.
• Strong instincts for reconciliation, control totals, data quality and traceability. You do not accept that two numbers are merely “close enough.”
• Ability to work through incomplete requirements, ask precise questions and turn business definitions into durable, testable logic with clear technical documentation.
• Financial services, wealth management, investment management or RIA ecosystem experience is strongly preferred.

• Location
• In Office / Hybrid - New York, NY.