Our industry recognition includes
21x Google Cloud Partner of the Year awards in the last 8 years.
3x AWS AI/ML award wins.
3x NVIDIA Partner of the Year titles.
2x Snowflake Partner of the Year awards.
Top analyst recognitions from Gartner, ISG, and Everest Group.
Consecutive certifications as a Great Place to Work.
Be part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.
Your next big opportunity starts here!
Work Location: New York, USA
Experience Level: 8+ years
Employment Type: Full time
Role Summary
We are seeking an experienced Senior ATA – Data to bridge the gap between enterprise data architecture, execution, and product delivery. In this dual-impact technical leadership role, you will architect scalable cloud data pipelines and datalakes while driving core technical product and program management workflows.
The ideal candidate brings deep domain expertise in financial services—specifically alternative investments—paired with senior-level hands-on data engineering chops (Snowflake, Python, advanced SQL) and proven delivery acumen across the full software and data development lifecycle.
Responsibilities
Cloud-Native Data Platforms: Architect, construct, and maintain resilient cloud data pipelines and modern datalake environments powered by Snowflake.
ETL/ELT Pipeline Development: Design and manage automated, high-throughput ingestions and transformations across structured, semi-structured, and unstructured financial datasets.
Legacy Modernization & Migration: Lead migration initiatives from legacy data stores to modern data architectures, establishing robust data mapping frameworks, transformation logic, and architectural consistency.
Data Quality & Integrity: Implement end-to-end data reconciliation, schema validation, de-duplication, and financial data integrity checks supporting mission-critical analytics and regulatory reporting.
Roadmapping & Prioritization: Drive product roadmaps, groom and prioritize technical backlogs, and balance feature delivery against technical debt and platform reliability.
Full-Lifecycle Execution: Spearhead initiatives across all phases—from business requirements gathering and technical design through development, integration testing, user acceptance testing (UAT), cutover planning, and go-live execution.
Agile Orchestration: Break down high-level strategic objectives into epics, technical user stories, and acceptance criteria in Jira.
Stakeholder Management & Change Enablement: Serve as the central conduit between business users, quant/analytics teams, and engineering leads; proactively escalate risks, align timelines, and ensure operational readiness during platform rollouts.
Required Skills
8+ years of hands-on data engineering, technical product management, or technical architecture experience.
Strong domain knowledge of financial services, with direct experience handling sensitive financial data within the alternative investments space (e.g., Private Equity, Hedge Funds, Private Credit, Real Estate).
8+ years of production-grade Python development focusing on large-scale data processing, performance optimization, and automation using libraries such as Pandas, Polars, PySpark, or equivalent.
8+ years writing advanced SQL, including deep expertise in complex Window Functions, Common Table Expressions (CTEs), recursive queries, dynamic conditional logic, and database query optimization.
Demonstrated production experience deploying and optimizing solutions on Snowflake and associated cloud ecosystems (AWS, Azure, or GCP).
Proven background managing end-to-end project lifecycles, release management, operational cutover plans, and Jira/Confluence delivery frameworks.
Experience designing automated continuous reconciliation frameworks for complex accounting, portfolio, or transactional data.
Familiarity with modern orchestration tools (e.g., Airflow, Prefect, Dagster) and data transformation frameworks (e.g., dbt).
Experience navigating regulatory and governance standards (e.g., SOC2, GDPR, BCBS 239) within buy-side or sell-side financial institutions.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Finance, or a related quantitative discipline.
What is in it for you
Be part of the fastest-growing AI-first digital transformation and engineering company in the world
Be a part of an energetic team of highly dynamic and talented individuals
Exposure to working with fortune 500 companies and innovative market disruptors
Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
