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Lead Data Engineer, Investment Data Platform
Castleton Tower Consulting, LLC. Design and build the warehouse and lakehouse, data models, orchestration, and semantic layers for the investment organization .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and architecting data models and orchestration solutions for investment organizations, with a strong focus on Python, SQL, and modern data platforms. Proven ability to lead technical teams, establish best practices in software engineering, and deliver high-quality data products.
Highest-signal resume keywords
Expert SQLExpert PythonProduction Experience with SnowflakeProduction Experience with dbtExperience with Dagster or Airflow
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringAnalytics EngineeringData ModelingSoftware EngineeringCI/CDAutomated TestingVersion ControlData Quality ControlsOrchestration SolutionsMonitoring and Alerting
Soft Skills
Clear CommunicationMentoringLeadership
Tools & Technologies
SnowflakeDatabricksDbtDagsterAirflowAzure Data ServicesPower BIClaude CodeCodexCursor
Industry Keywords
Investment Management SystemsPrivate Markets DataAsset AllocatorsAsset ManagersHedge FundsFinancial Data Providers
Tech Stack
Tools & technologiesAirflowAzurePythonSQL
About the role
Key responsibilities & impact- Design and build the warehouse and lakehouse, data models, orchestration, and semantic layers for the investment organization
- Build production-grade Python, SQL, dbt, and orchestration solutions, including batch and near-real-time pipelines
- Establish code review, testing, CI/CD, documentation, observability, and data quality controls
- Lead and mentor engineers through design reviews and pairing
- Set technical direction and own outcomes end to end
- Partner with investment, operations, finance, and reporting stakeholders to create durable data products
- Use Claude Code, Codex, Cursor, and Copilot to accelerate engineering while maintaining quality and controls
- Architect and build investment data domains including security and entity reference data, positions and transactions, performance, risk, and private-markets fund data
- Design correct, reconcilable, point-in-time-aware data models with tests and controls
- Own platform reliability, performance, and cost, including monitoring, alerting, and incident follow-through
- Review engineering work and improve subsequent versions
- Evaluate Snowflake, dbt, Dagster/Airflow, and Azure tooling and make build-versus-buy decisions
- Work closely with the client’s engineering leadership and investment, operations, and technology stakeholders
- Spend regular time in the office and approximately one week per month on-site with the client
Requirements
What you’ll need- 8+ years of hands-on experience in data engineering, analytics engineering, or software engineering focused on data platforms
- 3+ years leading technical work as a tech lead, principal or staff engineer, or engineering manager who still builds
- Expert SQL and Python
- Deep data modeling and architecture judgment beyond any single tool
- Production experience with modern warehouse and lakehouse platforms such as Snowflake or Databricks
- Production experience with dbt
- Production experience with orchestration tools such as Dagster or Airflow
- Strong software engineering practice including version control, code review, automated testing, and CI/CD applied to data
- Track record of shipping and operating systems built, described in terms of delivered outcomes
- Experience with investment management systems and data is strongly valued
- Experience with private markets data is strongly valued
- Experience with Azure data services and Power BI is strongly valued
- Experience in asset allocators, asset managers, hedge funds, private markets firms, or financial data providers is strongly valued
- Clear communication with engineers and investment professionals
- Authorization to work in the United States
Benefits
Comp & perks- Competitive total compensation commensurate with experience
- Full-time placement
- Hybrid work arrangement
- Regular time in the office
- Approximately one week per month of on-site client work