Data Engineer

• Design, build, and maintain scalable data pipelines and ETL processes to enable reliable data integration and analytics
• Architect and implement robust data storage solutions, including data warehouses, data lakes, and databases
• Partner closely with AI engineers, data analysts, and other cross-functional stakeholders to understand data requirements and deliver solutions that meet business needs
• Optimize and tune data systems to ensure high performance, reliability, and scalability
• Ensure data quality, accuracy, and integrity through rigorous testing, validation, and monitoring
• Establish, document, and enforce data governance standards and best practices
• Stay current on emerging data technologies and industry trends, and evaluate their applicability to our data platform
• Troubleshoot and resolve data-related issues efficiently to minimize disruption and maintain trust in our data systems

Senior Data Engineer

• Deploy new data pipelines
• Design & build data observability platforms and metrics
• Build metadata driven pipeline solutions
• Monitor and optimize data transformations
• Build third party data integrations

• Own End-to-End Delivery of Core Data Platform Components
• Design and ship the data normalization, schema mapping, validation, enrichment, and distribution pipeline for a net-new intelligent data warehouse
• Write production code as a hands-on individual contributor. This is not a role that delegates implementation to others
• Take technical ownership from architecture through deployment, with accountability for reliability, performance, and correctness
• Drive Technical Architecture
• Partner with a small seed team of senior engineers to define the end-to-end architecture for an AI-native data warehouse serving institutional financial clients
• Bring opinionated decisions on schema design, normalization strategies, API exposure patterns, and data distribution approaches
• Evaluate and select technologies with a bias toward what ships well and scales sustainably
• Build AI Evaluation Infrastructure
• Design and implement the evaluation framework that makes AI-generated outputs trustworthy in high-stakes financial data contexts
• Build cross-model comparison tooling, deterministic validation checks, and human-in-the-loop review workflows
• Contribute to shared AI infrastructure that will serve as a foundation for multiple products across the company
• Ship with AI-Native Development Practices
• Use agentic coding tools and LLM-assisted development as your primary workflow; this is how the entire team operates
• Bring strong opinions about how to get the most out of AI-assisted development while maintaining quality and reliability
• Contribute to the team’s evolving practices around AI-accelerated SDLC
• Establish Technical Standards
• As an early senior voice on a new team, set coding standards, review practices, and architectural documentation that will scale
• Help define what “good” looks like for a team building at speed without sacrificing quality
• Mentor and provide technical guidance as the team grows from seed squad to full delivery organization
• Collaborate Across Engineering and Product
• Work closely with your engineering manager, peer engineers, and product management to translate requirements into executable technical plans
• Participate actively in design reviews and roadmap discussions with grounded, implementation-level perspective
• Engage directly with the nuances of private markets data – fund administration, investment data schemas, institutional reporting workflows – to build domain intuition that improves your technical decisions

Staff Software Engineer, Data Platform

• You will work closely with finance, accounting, billing, and revenue teams to understand their main pain points and translate them into self-serve, reliable, and scalable data solutions
• You are expected to mentor other team members and be a champion of engineering excellence across the organization
• You will be part of a small team with a large amount of ownership and autonomy, managing initiatives directly from design through execution
• You will have the freedom to suggest and drive organization-wide initiatives that shape the financial data vision and roadmap
• You will own critical data integration pipelines and models, ensuring uniform, reliable, timely, and accurate financial reporting

Senior Data Engineer, Finance

• Design and maintain enterprise data architecture standards leveraging Snowflake.
• Collaborate with SAP data teams to ensure seamless data ingestion from SAP and non-SAP sources.
• Develop scalable data modeling frameworks, including medallion architectures for enterprise data products.
• Establish data performance, cost optimization, and security standards across the Snowflake environment.
• Guide integration with Power BI and other analytics platforms for efficient data delivery.
• Mentor engineering teams on Snowflake data patterns, performance tuning, and governance best practices.

Senior Principal Data Architect

• Developing and governing the Bank’s batch data architecture, including defining standards, tools, and models that support secure, scalable, and efficient data capture, integration, storage, and delivery.
• Identifying data-related business requirements, creating high level enterprise and sub architecture models, and optimizing data flows to reduce redundancy and improve accessibility within security boundaries.
• Supporting the Data Development team by designing and implementing ETL workflows using Informatica PowerCenter/IDMC, Oracle Database, ActiveBatch enterprise schedulers, and related technologies, contributing to requirements analysis, development, testing, deployment, and ongoing support.
• Serving as a technical expert and mentor, providing architectural leadership, guidance, and best practices to ensure consistent, high quality data solutions across the organization.

Data Architect

• Design the vision and blueprint of an organization’s data framework.
• Design and manage data systems, set policies for how data is stored and accessed, coordinate various data sources within an organization, and integrate new data technologies into existing IT infrastructures.
• Data modeling and design, including software development and database administration.

Data Architect – Data Ecosystems

• Lead a team of data engineers responsible for designing, building, and maintaining scalable data pipelines
• Collaborate with cross-functional teams to ensure high-quality, reliable data flows
• Monitor project progress and report findings to the leadership team
• Conduct work performance reviews, ensuring adherence to Company standards
• Advocate for data quality, security, and performance improvements

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