B.S. or M.S. in Computer Science, IT, Statistics, Mathematics, or Management Information Systems
Advanced SQL querying and scripting skills
Strong proficiency in Python and knowledge of OOP and Design Patterns
Experience with modern data platforms like Snowflake or Databricks
Familiarity with data orchestration tools such as Dagster or Airflow
Understanding of data warehousing methodologies and modeling practices
Proven experience in Data Engineering or Data Analytics teams for product companies
Responsibilities
Design and implement data models and pipelines on Chatham's Data Platform
Collaborate with teams to enhance their analytical service usage
Review existing Cloud Data Platform components for improvement
Participate in data modeling activities for effective data structures
Evaluate work of other Data Engineers for alignment with business requirements
Support data analysts and scientists in complex analytics solutions
Identify and resolve data-related issues collaboratively
Benefits
Opportunity to work on innovative fintech solutions
Collaborative and cross-functional team environment
Exposure to advanced cloud technologies and data platforms
Professional development and growth opportunities
Impactful role in enhancing data-driven decision-making
Full Job Description
Job Description:
Overview:
The technology team at Chatham is responsible for building scalable, innovative fintech solutions that power global investment decisions. As a Data Engineer, within the Product Engineering department, you will contribute to Data Engineering solutions & infrastructure underpinning products that Chatham Financial exposes to its clients or to its internal users. Reporting to the Senior Data Analyst (TL), you will implement cloud services and capabilities that reliably expose data at scale, enabling AI-first programmatic analytics for critical use-cases.
In this role you will:
Design and implement data models, pipelines, transformations, and analytics across Chatham's Data Platform using a mix of Python, .NET, Snowflake and Cube Core
Pair with other teams to supercharge their usage of analytical services that enable them to ship critical use-cases
Participate in reviewing existing components/features of the Cloud Data Platform periodically with more-experienced Data Engineers and support them in executing against improvement plans
Participate in data modelling activities to design efficient and effective data structures that support data analysis and reporting requirements.
Review work done by other Data Engineers from the perspective of data warehouse integration practices, data modeling practices, degree of alignment to and/or completeness of business requirements
Collaborate with data analysts and data scientists to understand data requirements and provide support for complex Data Analytics solutions
Assist in identifying and resolving data-related issues and errors, working with the team to implement appropriate solutions.
Your impact:
As a Data Engineer, you will play a key role in building and evolving Chatham's data platforms by delivering modern, scalable and reliable data solutions. Your work will directly support analytics, product functionality, and client-facing capabilities while helping drive improvements in platform quality and performance.
Contributors to your success:
B.S. or M.S. studies in Computer Science/Information Technology / Statistics / Mathematics / Management Information Systems
Advanced SQL database querying and scripting
Strong knowledge of a scripting language (preferably Python) and proven knowledge of OOP and Design Patterns
Ability to contribute across codebases in multiple programming languages employed in micro-service development or similar (such as Python, .NET)
Strong knowledge of dbt (data build tool) or similar transformation frameworks such as SQLMesh or Dataform
Hands-on experience with at least one modern data platform, preferably Snowflake; experience with Databricks or Microsoft Fabric is also relevant
Hands-on experience with building highly scalable data querying/retrieval Web Services, employing tooling such as Cube Core or similar (Power BI Tabular Models, Looker ML etc.)
Hands-on experience with at least one modern data orchestration product, preferably Dagster; experience with Prefect or Airflow is also relevant
Experience with Azure cloud and web services, ideally Azure Container Apps or similar
Experience with CI/CD pipelines, preferably GitHub-based
Experience with Cube Core represents a big plus
Experience applying AI and automation tools in day-to-day engineering work represents a big plus
Proven previous experience in working as part of Data Engineering or Data Analytics teams for Product companies creating data-oriented software solutions
Good understanding of data warehousing methodologies (Kimball, Inmon, Data Vault 2.0)
Good understanding of data modelling practices (relational, entity-relationship, object-oriented, flat, query-first)
Good understanding of data engineering design patterns (raw loads, replication, batch ETL, streaming ETL, ELT, stream processing, data virtualization, change data capture)
Strong knowledge of a typical SDLC
Must be a self-starter, with the ability to work independently, with different groups and teams, utilizing solid communication skills.
Ability to work in cross-functional teams
About Chatham Financial
Chatham Financial is a global financial risk management advisory and technology solutions firm. The company provides a range of services, including debt and derivatives advisory, hedge accounting and regulatory compliance, and technology solutions for financial risk management. Chatham Financial was founded in 1991 and is headquartered in Kennett Square, Pennsylvania. The company serves clients in a wide range of industries, including real estate, private equity, and renewable energy.
