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Senior Data Solutions Engineer

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design and implement data pipelines, transformations, models and integrations on the Data Platform

  • Design, model and onboard datasets required by client and product solutions

  • Implement and maintain data quality checks and validation processes

  • Review and improve existing platform components for scale, reliability and performance

  • Participate in code reviews and mentor less experienced engineers

From the employer’s posting
Design and implement data pipelines, transformations, models, and integrations across Chatham’s Data Platform
Design, model, and onboard datasets required by client and product solutions
Implement and maintain data quality checks, validation processes, and appropriate engineering controls
Review and improve existing platform components, identifying opportunities for scalability, reliability, performance, and maintainability
Participate in code reviews and provide guidance and mentorship to less experienced engineers where appropriate

About Chathamfinancial

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

Apply at Chathamfinancial

Posting record

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Status in our records
Live
First seen by us
Oct 8, 202627 days ago
Recorded sightings
20
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 27

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.

Chathamfinancial is hiring

5 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down quickly
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • dbt
  • Oracle
  • PostgreSQL
  • Power BI
  • Redshift
  • S3
  • Snowflake
  • SQL Server
  • Terraform
Where the posting names them
- Proven understanding of Data Ops/DevSecOps/DevOps and how to properly implement, deploy, use & improve - Experience building Python-based data processing components or services in cloud environments (ideally Azure App Functions) - Proven understanding of how data architecture interacts with broader technical, business, and security architecture
- Data Integration & Orchestration (one of the following: dbt, SQLMesh, StreamSets, Apache NiFi, Informatica, Talend, SSIS – legacy experience beneficial, list not exhaustive) - RDBMS (one of the following: PostgreSQL, Microsoft SQL Server, Oracle, IBM DB2 – list not exhaustive) - Storage (one of the following: Azure Blob, Azure Data Lake, AWS S3, Google Storage, general HDFS – list not exhaustive)
- RDBMS (one of the following: PostgreSQL, Microsoft SQL Server, Oracle, IBM DB2 – list not exhaustive) - Storage (one of the following: Azure Blob, Azure Data Lake, AWS S3, Google Storage, general HDFS – list not exhaustive) - Data Ops/DevSecOps/DevOps based on GitHub Actions or similar
- Proven understanding of how data architecture interacts with broader technical, business, and security architecture - 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, StreamSets, Apache NiFi, Informatica, Talend, SSIS – legacy experience beneficial, list not exhaustive)
- 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, StreamSets, Apache NiFi, Informatica, Talend, SSIS – legacy experience beneficial, list not exhaustive) - RDBMS (one of the following: PostgreSQL, Microsoft SQL Server, Oracle, IBM DB2 – list not exhaustive)
In this role you will: - Design and implement data pipelines, transformations, models, and integrations across Chatham’s Data Platform using a mix of Snowflake and Power BI based solutions - Design, model, and onboard datasets required by client and product solutions
- Deep understanding of data engineering design patterns (raw loads, replication, batch ETL, streaming ETL, ELT, stream processing, data virtualization, change data capture) - Great understanding of declarative & imperative database deployment patterns and proven usage of tools like Flyway or Terraform or anything else similar - Proven understanding of Data Ops/DevSecOps/DevOps and how to properly implement, deploy, use & improve

Your next step

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About the role

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.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

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

View original posting ↗

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. 

In this role you will:

 

  • Design and implement data pipelines, transformations, models, and integrations across Chatham’s Data Platform using a mix of Snowflake and Power BI based solutions
  • Design, model, and onboard datasets required by client and product solutions
  • Work closely with the squad’s Tech Lead and Data Analyst to translate solution requirements into reliable Data Platform based implementations
  • Review and improve existing platform components, identifying opportunities for scalability, reliability, performance, and maintainability
  • Implement and maintain data quality checks, validation processes, and appropriate engineering controls
  • Contribute to solution design discussions and provide Data Engineering expertise on implementation approaches and trade-offs
  • Follow and contribute to Data Engineering standards and best practices across development, testing, deployment, and operations
  • Participate in code reviews and provide guidance and mentorship to less experienced engineers where appropriate

 

Your impact:

 

As a Senior Data Engineer, you will play a key role in turning complex client and product requirements into reliable, scalable Data Engineering solutions. Working alongside the squad’s Tech Lead and Data Analyst, you will take ownership of the engineering components required to onboard, transform, validate, and expose data through Chatham’s Asset Platform. Your work will ensure that solutions are robust, maintainable, and aligned with established platform standards.

 

Contributors to your success:

 

  • B.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)
  • Great understanding of declarative & imperative database deployment patterns and proven usage of tools like Flyway or Terraform or anything else similar
  • Proven understanding of Data Ops/DevSecOps/DevOps and how to properly implement, deploy, use & improve
  • Experience building Python-based data processing components or services in cloud environments (ideally Azure App Functions)
  • Proven understanding of how data architecture interacts with broader technical, business, and security architecture
  • 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, StreamSets, Apache NiFi, Informatica, Talend, SSIS – legacy experience beneficial, list not exhaustive)
    • RDBMS (one of the following: PostgreSQL, Microsoft SQL Server, Oracle, IBM DB2 – list not exhaustive)
    • Storage (one of the following: Azure Blob, Azure Data Lake, AWS S3, Google Storage, general HDFS – 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.

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