Senior Data Engineer, Asset Platform

Job Description:

Overview:

We don’t simply hire employees. We invest in them. When you work at Chatham, we empower you — offering professional development opportunities to help you grow in your career, no matter if you've been here for five months or 15 years. Chatham has worked hard to create a distinct work environment that values people, teamwork, integrity, and client service. You will have immediate opportunities to partner with talented subject matter experts, work on complex projects, and contribute to the value Chatham delivers every day. 

The technology team at Chatham is responsible for building scalable, innovative fintech solutions that power global investment decisions. As a Senior Data Engineer, within the Product Engineering department, you will contribute to and take ownership of Data Engineering solutions & infrastructure underpinning products that Chatham Financial exposes to its clients or to its internal users. You will work closely with other engineers and technical leaders to design, implement, and evolve reliable and scalable Data Engineering solutions.

In this role you will:

• Design and implement new Cloud Data Platform features using a mix of SQL, Python and dbt

• Lead the review of existing components/features of the Cloud Data Platform, identify opportunities for improvement, and drive the implementation of improvements related to scalability, reliability, performance, and maintainability

• Lead data modelling activities to design efficient and effective data structures that support data analysis, reporting, and product requirements

• Design and implement Power BI solutions, including semantic models, Power Query transformations, and DAX, ensuring reporting and analytical requirements are supported by scalable and well-designed data structures

• Review work done by other Data Engineers from the perspective of data warehouse integration practices, data modelling practices, engineering quality, and degree of alignment to and/or completeness of business requirements

• Use version control systems like Git to collaborate with the team on code development and ensure proper versioning of Data Engineering artifacts

• Collaborate with data analysts, data scientists, software engineers, and other stakeholders to understand data requirements and translate them into appropriate Data Engineering solutions

• Independently identify, investigate, and resolve complex data-related issues, working across teams where appropriate to determine root causes and implement sustainable solutions

• Contribute to technical and architectural decisions, evaluating implementation approaches and technical trade-offs from a Data Engineering perspective

• Establish, promote, and improve Data Engineering practices and standards across development, testing, deployment, observability, and operations

• Participate in code and design reviews and provide technical guidance and mentorship to less experienced Data Engineers

Your impact:

As a Senior Data Engineer, you will play a key role in designing, building, and evolving Chatham’s data platforms by delivering scalable, reliable, and well-modelled data solutions. You will take ownership of Data Engineering components, ensuring they align with business needs and engineering best practices. Your work will support analytics, product functionality, and client-facing capabilities while driving improvements in platform quality, performance, and maintainability.

Contributors to your success:

• B.S. or M.S. in Statistics / Mathematics / Economics / Computer Science / Management Information SystemsB.S. or M.S. in Statistics / Mathematics / Economics / Computer Science / Management Information Systems

• Deep understanding of data warehousing methodologies (Kimball, Inmon, Data Vault 2.0), with an emphasis on Dimensional Data Warehousing

• Deep understanding of data modelling (relational, entity-relationship, object-oriented, flat, query-first)

• Deep understanding of data engineering design patterns (raw loads, replication, batch ETL, streaming ETL, ELT, stream processing, data virtualization, change data capture)

• Proven understanding of DataOps / DevSecOps / DevOps practices and how to properly implement, deploy, operate, and continuously improve Data Engineering solutions

• Experience building Python-based data processing components or services in cloud environments, ideally using Azure Functions or Azure App Services

• Expert-level SQL database querying and scripting skills, with the ability to design, optimize, and troubleshoot complex data workloads

• Advanced hands-on experience with Power BI and Microsoft Fabric, including semantic model design and optimization, Power Query, advanced DAX, role-playing dimensions, calculation groups, Row-Level Security (RLS), Dataflows Gen2, and external tooling such as DAX Studio

• Strong understanding of Power BI semantic model optimization techniques, including DAX performance tuning, model design, storage considerations, and efficient query patterns

• Proven previous experience working as part of Data Engineering, Data Integration, or Business Intelligence teams within product-focused organizations building data-oriented software solutions

• Proven understanding of how data architecture interacts with broader technical, business, and security architecture

• Strong knowledge of the Software Development Lifecycle (SDLC), including development, testing, deployment, release management, observability, and ongoing support

• Experience applying AI and automation tools to Data Engineering and software development workflows, including agentic engineering approaches that improve development productivity, code quality, testing, troubleshooting, or operational efficiency

• Ability to design and implement Data Engineering solutions, evaluate technical trade-offs, contribute to architectural decisions, and continuously improve engineering practices using at least one tool/software/technology from each of the following areas:

• Cloud Data Warehouse / Lakehouse Platforms (Snowflake preferable, but open to the following as well: Microsoft Fabric, Databricks, Amazon Redshift – list not exhaustive)

• Data Integration & Orchestration (one of the following: dbt, SQLMesh – legacy experience beneficial, list not exhaustive)

• RDBMS (one of the following: PostgreSQL, Microsoft SQL Server – list not exhaustive)

• Storage (one of the following: Azure Blob, Azure Data Lake, AWS S3, Google Storage – list not exhaustive)

• Database Deployment & Infrastructure as Code (one of the following: Terraform, Flyway, Liquibase, SchemaChange – list not exhaustive)

• Data Ops/DevSecOps/DevOps based on GitHub Actions or similar

About Chatham Financial:

Chatham Financial is the leading independent capital markets advisor, delivering an integrated blend of expert advice and powerful technology to help you reduce risk and seize opportunity. With decades of capital markets strategy, execution, monitoring, and performance expertise, we serve as an unwavering advocate for your best interests and your innovation partner. Our technology platform unifies data across assets, debt, and derivatives, giving you unmatched agility, transparency, and insight.

It’s clear ahead.

Our commitment is to carry that light forward in every partnership, every solution, and every market we serve.

We help guide the way—giving clients the insight and momentum to move forward with confidence, no matter what lies ahead.