Data Engineer, Asset Platform

Chatham Financial

Data Engineer building scalable data platforms for Chatham Financial, a capital-markets advisor using technology to reduce risk and seize opportunity. Developing pipelines, models, and cloud data solutions supporting analytics and client products.

Posted 8/14/2026full-timeRemote • 🇷🇴 RomaniaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in SQL and Python for implementing cloud data platform features, along with strong knowledge of data modeling and engineering design patterns. Proficient in collaborating with cross-functional teams to support data analysis and reporting while ensuring data quality and performance.

Highest-signal resume keywords

Advanced SQL Database QueryingPython ScriptingData Engineering Design PatternsVersion Control with GitData Warehousing Methodologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData ModelingData IntegrationData WarehousingObject-Oriented ProgrammingETLData VirtualizationChange Data CaptureAnalytical Skills

Soft Skills

Strong Communication SkillsSelf-StarterAbility to Work IndependentlyCross-Functional Team CollaborationPeople Skills

Tools & Technologies

GitTerraformSnowflakeDbtDockerAzure Container AppsAzure Event HubsPower BIDagsterAirflow

Industry Keywords

Cloud Data PlatformData EngineeringBusiness IntelligenceData-Oriented Software SolutionsSDLC

Tech Stack

Tools & technologies

AirflowAzureCloudDockerETLPythonSDLCSQLTerraformVault

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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