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Chatham Financial

Global financial risk advisory and technology

Data Engineer

Data EngineeringUpdated on Nov 12
Full-timeKennett Square, PA, USANo salary listedIn-person

About the Job

Requirements

  • B.S. or M.S. studies in Computer Science, Information Technology, Statistics, Mathematics, or Management Information Systems.
  • Advanced SQL database querying and scripting skills.
  • Strong knowledge of a scripting language, preferably Python, and proven knowledge of object-oriented programming and design patterns.
  • Ability to contribute across codebases in multiple programming languages used in microservice development or similar, such as Python and .NET.
  • Strong knowledge of dbt or similar transformation frameworks such as SQLMesh or Dataform.
  • Hands-on experience with at least one modern data platform, preferably Snowflake; Databricks or Microsoft Fabric experience is also relevant.
  • Hands-on experience building highly scalable data querying and retrieval web services using tooling such as Cube Core or similar, including Power BI Tabular Models or Looker ML.
  • Hands-on experience with at least one modern data orchestration product, preferably Dagster; Prefect or Airflow experience is also relevant.
  • Experience with Azure cloud and web services, ideally Azure Container Apps or similar.
  • Experience with CI/CD pipelines, preferably GitHub-based.
  • Previous experience working as part of Data Engineering or Data Analytics teams at product companies creating data-oriented software solutions.
  • Understanding of data warehousing methodologies, including Kimball, Inmon, and Data Vault 2.0.
  • Understanding of data modelling practices, including relational, entity-relationship, object-oriented, flat, and query-first approaches.
  • Understanding of data engineering design patterns, including raw loads, replication, batch ETL, streaming ETL, ELT, stream processing, data virtualization, and change data capture.
  • Strong knowledge of a typical software development life cycle.
  • Ability to work independently and with different groups and teams.
  • Ability to work in cross-functional teams.

Responsibilities

  • Design and implement data models, pipelines, transformations, and analytics across the Data Platform using Python, .NET, Snowflake, and Cube Core.
  • Pair with other teams to help them use analytical services to deliver critical use cases.
  • Periodically review existing Cloud Data Platform components and features with more experienced Data Engineers and support execution of improvement plans.
  • Participate in data modelling activities to design efficient data structures that support data analysis and reporting requirements.
  • Review other Data Engineers’ work for data warehouse integration and data modelling practices, and alignment with or completeness of business requirements.
  • Collaborate with data analysts and data scientists to understand data requirements and support complex Data Analytics solutions.
  • Help identify and resolve data-related issues and errors, working with the team to implement appropriate solutions.
  • Build and evolve data platforms by delivering modern, scalable, and reliable data solutions that support analytics, product functionality, and client-facing capabilities while improving platform quality and performance.

Desired Qualifications

  • Experience with Cube Core.
  • Experience applying AI and automation tools in day-to-day engineering work.
  • Experience with Snowflake is preferred; Databricks or Microsoft Fabric experience is also relevant.
  • Dagster is preferred; Prefect or Airflow experience is also relevant.
  • Azure Container Apps experience or similar is preferred.
  • GitHub-based CI/CD experience is preferred.
  • Python is the preferred scripting language.

About the Company

Chatham Financial

Global financial risk advisory and technology

Chatham Financial provides advisory services and technology solutions to help organizations manage financial risk across global markets. Its approach blends tailored risk-management strategies with software platforms and subscription-based tools, plus transaction-based services. Distinct from many peers, it leverages a large global network (working with over 3,000 firms) to deliver customized, cross-market risk solutions. Its goal is to help clients navigate capital markets, reduce financial risk exposure, and improve financial outcomes.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Kennett Square, PA
Founded
1992

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