Data Engineer, Asset Platform

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Chatham Financial

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1991

Chatham Financial is the leading independent capital markets advisor, delivering an integrated blend of expert advice and powerful technology to help organizations reduce risk and seize opportunity. With decades of experience across strategy, execution, monitoring, and performance, we serve as an innovation partner and advocate for our clients. Our platform unifies data across assets, debt, and derivatives, providing the clarity and insight needed to make confident decisions. Founded in 1991, Chatham serves more than 4,500 companies worldwide, supporting $2 trillion in annual transaction volume. To learn more, visit chathamfinancial.com.

📋 Description

• Implement new Cloud Data Platform features using SQL, Python, and dbt • Participate in periodic reviews of Cloud Data Platform components and support improvement plans • Participate in data modelling activities to design efficient data structures for analysis and reporting • Review other Data Engineers’ work for data warehouse integration, data modeling, and business-requirement alignment • Use Git and version control to collaborate on code development and version data engineering artifacts • Collaborate with data analysts and data scientists to understand requirements and support analysis and reporting • Identify and resolve data-related issues and errors • Build and evolve scalable, reliable, well-modelled data solutions and pipelines • Support analytics, product functionality, and client-facing capabilities while improving platform quality and performance • Report to the Senior Data Engineer (TL)

🎯 Requirements

• B.S. or M.S. studies in Computer Science, Information Technology, Statistics, Mathematics, or Management Information Systems • Advanced SQL database querying and scripting • Strong knowledge of a scripting language, preferably Python • Proven knowledge of object-oriented programming and design patterns • Experience with version control systems such as Git • Experience with data engineering, data integration, or business intelligence teams at product companies creating data-oriented software solutions • Good understanding of data warehousing methodologies, including Kimball, Inmon, and Data Vault 2.0 • Good understanding of data modelling practices, including relational, entity-relationship, object-oriented, flat, and query-first models • Good understanding of data engineering design patterns, including raw loads, replication, batch ETL, streaming ETL, ELT, stream processing, data virtualization, and change data capture • Understanding of declarative and imperative database deployment patterns • Proven usage of tools such as Terraform, Flyway, Schema Change, Liquibase, or similar • Strong analytical skills in collecting, organizing, and analyzing significant amounts of data • Strong knowledge of a typical SDLC • Self-starter able to work independently and with different groups and teams • Ability to work in cross-functional teams • Strong communication and people skills • Experience with onsite/offshore working models • Experience with Snowflake, dbt/SQLMesh/Dataform, Dagster/Prefect/Airflow, Docker, Azure Container Apps/Azure App Functions, Azure Event Hubs, or Power BI Semantic Models is a plus

🏖️ Benefits

• Professional development opportunities • Opportunities to partner with talented subject matter experts • Opportunities to work on complex projects • Opportunities to contribute to client value and innovation