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Bucharest
Live, first seen by us 69 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
As a Data Engineer, within the Product Engineering department, you will report to the Senior Data Engineer (TL)
Implement new Cloud Data Platform features using SQL, Python and dbt
Take part in data modelling to design data structures for analysis and reporting
Review other Data Engineers' work for warehouse integration and modelling practices
Use Git to version data engineering code and artifacts
Support analysts and data scientists on data requirements and reporting
Help with implementing new Cloud Data Platform features using a mix of SQL, Python and dbt
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
Use version control systems like Git to collaborate with the team on code development and ensure proper versioning of data engineering artifacts
Collaborate with data analysts and data scientists to understand data requirements and provide support for data analysis and reporting
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.
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Day 69
Up longer than most. Similar jobs usually come down between day 5 and day 54.
From 10,733 similar postings that came down. Coming down is not always a hire.
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In this role you will: • Help with implementing new Cloud Data Platform features using a mix of SQL, Python and dbt • 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
• 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 platform, preferably Snowflake; experience with Databricks or Microsoft Fabric is also relevant
• 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 Power BI, across Power Query and using DAX against Semantic Models • Experience with Azure cloud and web services, ideally Azure Functions and Azure App Services • Experience with CI/CD pipelines, preferably GitHub-based
• 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 platform, preferably Snowflake; experience with Databricks or Microsoft Fabric is also relevant • Practical experience with 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 • Practical experience with dbt (data build tool) or similar transformation frameworks such as SQLMesh or Dataform • Hands-on experience with Power BI, across Power Query and using DAX against Semantic Models
• Practical experience with dbt (data build tool) or similar transformation frameworks such as SQLMesh or Dataform • Hands-on experience with Power BI, across Power Query and using DAX against Semantic Models • Experience with Azure cloud and web services, ideally Azure Functions and Azure App Services
• Experience with CI/CD pipelines, preferably GitHub-based • Experience with Dagster / Prefect / Airflow represents a big plus • Experience applying AI and automation tools in day-to-day engineering work represents a big plus
• Good understanding of data engineering design patterns (raw loads, replication, batch ETL, streaming ETL, ELT, stream processing, data virtualization, change data capture) • Understanding of declarative & imperative database deployment patterns and proven usage of tools like Terraform, Flyway, Schema Change, Liquibase or anything else similar • Strong analytical skills in collecting, organizing, and analyzing significant amounts of data
Complete your application on chathamfinancial.wd501.myworkdayjobs.com. The employer’s form will show what is required.
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Yes. We’ve followed one other Data Engineer, Asset Platform job there since August 2026. It came down after 9 days.
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 report to the Senior Data Engineer (TL) and contribute to Data Engineering solutions & infrastructure underpinning products that Chatham Financial exposes to its clients or to its internal users.
• Help with implementing new Cloud Data Platform features using a mix of SQL, Python and dbt
• 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
• Use version control systems like Git to collaborate with the team on code development and ensure proper versioning of data engineering artifacts
• Collaborate with data analysts and data scientists to understand data requirements and provide support for data analysis and reporting
• Assist in identifying and resolving data-related issues and errors, working with the team to implement appropriate solutions.
As a Data Engineer, you will play a key role in building and evolving Chatham’s data platforms by delivering scalable, reliable, and well-modelled data solutions. You will contribute to both product development and enablement initiatives, ensuring that data pipelines and models are aligned with business needs and engineering best practices. Your work will directly support analytics, product functionality, and client-facing capabilities while helping drive improvements in platform quality and performance.
• 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 platform, preferably Snowflake; experience with Databricks or Microsoft Fabric is also relevant
• Practical experience with dbt (data build tool) or similar transformation frameworks such as SQLMesh or Dataform
• Hands-on experience with Power BI, across Power Query and using DAX against Semantic Models
• Experience with Azure cloud and web services, ideally Azure Functions and Azure App Services
• Experience with CI/CD pipelines, preferably GitHub-based
• Experience with Dagster / Prefect / Airflow 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, Data Integration or Business Intelligence 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)
• Understanding of declarative & imperative database deployment patterns and proven usage of tools like Terraform, Flyway, Schema Change, Liquibase or anything else similar
• Strong analytical skills in collecting, organizing, and analyzing significant amounts of data
• 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
• Great communication and people skills with an experience of onsite/offshore model
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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Bucharest
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