Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Kennett Square
Actively hiring, first seen by us 7 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Design and implement data models, pipelines and transformations
Build cloud services that expose data at scale for analytics
Pair with other teams to make analytical services easier to use
Review other engineers' work on warehouse integration and data modeling
Help resolve data-related issues and errors
Design and implement data models, pipelines, transformations, and analytics across Chatham’s Data Platform
implement cloud services and capabilities that reliably expose data at scale
Pair with other teams to supercharge their usage of analytical services
Review work done by other Data Engineers from the perspective of data warehouse integration practices, data modeling practices
Assist in identifying and resolving data-related issues and errors
Advanced SQL database querying and scripting
Strong knowledge of a scripting language (preferably Python) and proven knowledge of OOP and Design Patterns
Strong knowledge of dbt (data build tool) or similar transformation frameworks
Hands-on experience with at least one modern data platform, preferably Snowflake
Hands-on experience with at least one modern data orchestration product, preferably Dagster
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.
In the employer’s words · Read in context
Actively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 7
Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
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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
- 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 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
- 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
- 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
- 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.)
- 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 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
- 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
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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 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:
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:
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.
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Kennett Square
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