Data Engineer, Investment Data Platform

Castleton Tower Consulting, LLC

. Build and maintain data pipelines and transformations in SQL and Python using dbt, Snowflake, and orchestration tools .

Posted 9/23/2026full-timeUnited StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining data pipelines using SQL and Python, with a strong focus on data modeling, ETL/ELT processes, and ensuring data quality through testing and reconciliation. Proficient in collaborating with cross-functional teams to deliver reliable datasets and reports, particularly in financial and investment domains.

Highest-signal resume keywords

SQLPythonData ModelingETL/ELTSnowflake

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringAnalytics EngineeringData Quality ChecksReconciliationCI/CDVersion ControlTestingMonitoringData TransformationData Pipeline Development

Soft Skills

Analytical AbilityAttention to Detail

Tools & Technologies

DbtSnowflakePower BIAzure Data ServicesAzure DevOpsAirflowDatabricks

Industry Keywords

Financial DataInvestment DataPrivate Equity Data

Tech Stack

Tools & technologies

AirflowAzureETLPythonSQL

About the role

Key responsibilities & impact

Build and maintain data pipelines and transformations in SQL and Python using dbt, Snowflake, and orchestration tools
Model investment and operational data, including positions, transactions, performance, reference data, and private-markets fund data
Write tests, data quality checks, and reconciliations to validate data accuracy
Fix root causes of data issues
Ship through code review and CI/CD
Monitor and maintain reliable production pipelines
Work with analysts and investment teams to understand requirements
Deliver trusted datasets and reports, including Power BI
Use AI-assisted development tools while maintaining quality
Collaborate with client engineering leadership and investment, operations, and technology stakeholders
Spend regular time in the office and perform on-site client work

Requirements

What you’ll need

3 to 5 years of hands-on experience in data engineering, analytics engineering, or a closely related software role
Strong SQL and Python
Solid grounding in data modeling and ETL/ELT
Experience with a modern data warehouse such as Snowflake, Synapse, Databricks, or similar
Experience with a transformation or orchestration tool such as dbt, ADF, Airflow, Dagster, or similar
Version control, code review, testing, and monitoring experience
Strong analytical ability and attention to detail
Exposure to financial, investment, or private equity data valued
Azure data services, Azure DevOps pipelines, or Power BI valued
Experience reconciling data across systems valued
Authorized to work in the United States

Benefits

Comp & perks

Competitive total compensation commensurate with experience
Full-time placement
Regular time in the office with client engineering leadership and stakeholders
Opportunity to learn from experienced builders
Real ownership and rapid growth opportunities
Direct feedback and professional growth toward senior engineer