Senior Data Engineer, Data Transformation Platform

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer, Data Transformation Platform based in the United States.

This is an opportunity to build and evolve the data infrastructure powering analytics and decision-making across the structured finance industry. As a senior member of a small, highly collaborative engineering team, you will design and maintain production-grade data pipelines that transform large volumes of complex financial data into reliable, actionable datasets. You will take ownership of data architecture, modeling, performance optimization, and platform modernization while helping establish scalable engineering practices. Working with Python, SQL, dbt, Spark, Google Cloud, and Databricks, you will contribute to critical technology initiatives from design through deployment. Your work will directly influence how financial institutions assess investment performance, understand risk, and make more informed decisions.

Accountabilities

• Design, develop, and maintain production data pipelines using Python, SQL, and dbt across Google Cloud Platform, including BigQuery, Cloud Composer, and Dataproc, as well as Databricks.

• Own data architecture, pipeline design, and data modeling to create scalable, reliable, and maintainable schemas and transformation workflows.

• Profile, troubleshoot, and optimize large-scale data processing jobs to improve performance, efficiency, and infrastructure costs.

• Lead roadmap initiatives from beginning to end, including developing new pipelines, migrating legacy workflows, and modernizing the underlying data platform.

• Maintain the health and reliability of production systems through pipeline monitoring, troubleshooting, root-cause analysis, and participation in an on-call rotation.

• Conduct code reviews, mentor engineers and analysts, and promote high standards of engineering quality and maintainability.

• Improve development practices and team tooling, including the adoption of AI-assisted development tools such as Claude Code.

• Collaborate with analysts, product teams, and other engineering groups to translate business and data requirements into accurate, sustainable data transformations.

• Proactively evaluate new technologies and identify opportunities to improve the platform's architecture, workflows, and operational performance.

Requirements:

• At least 7 years of experience designing, building, and operating production data pipelines and data platforms on a major cloud provider, preferably Google Cloud Platform (GCP).

• Strong data modeling and architecture capabilities, with a track record of designing pipelines and schemas that other engineers can maintain, understand, and extend.

• Advanced proficiency in Python and SQL, with hands-on experience using dbt and Apache Spark.

• Experience with Scala or Java is an advantage.

• Demonstrated ability to optimize large-scale data processing workloads, delivering measurable improvements in performance and cost efficiency.

• Experience managing deployment processes and orchestration for complex production data pipelines.

• Practical experience using Databricks for data pipelines and analytics, including workspace administration.

• Familiarity with cloud-based data services and technologies such as BigQuery, Cloud Composer, and Dataproc, or comparable solutions.

• Strong problem-solving and troubleshooting skills, with the ability to take ownership of production issues and identify their underlying causes.

• Self-directed working style, with the ability to operate independently, prioritize effectively, and make a meaningful impact within a small team.

• Excellent collaboration and communication skills, with the ability to work closely with technical and non-technical stakeholders.

• Curiosity about structured finance and financial markets. Previous financial industry experience is preferred but not required, as relevant domain knowledge can be developed on the job.

Benefits:

• Annual base salary range of $160,000–$175,000, with final compensation determined by experience, expertise, and other business considerations.

• Paid time off, including vacation days, personal holidays, paid sick leave, and company holidays.

• 401(k) retirement plan with company matching.

• Comprehensive medical, dental, and vision insurance for employees and their families.

• Paid parental leave: 10 weeks for all parents and 16 weeks for birthing parents, at 100% of salary.

• Fertility support with a lifetime maximum benefit of $25,000.

• Backup childcare support through Bright Horizons.

• Professional learning and development opportunities, including support for certifications, courses, graduate programs, and MBAs.

• Access to internal development and mentorship programs, including management and technical training academies.

• Gym and wellness memberships through Wellhub.

• Free mental health support through Spring Health and access to a confidential Employee Assistance Program.

• Annual home office allowance of $250.

• Pre-tax commuter benefits.

• Employee referral program offering rewards ranging from $2,500 to $10,000.

• Employee resource groups and opportunities to participate in community initiatives.

• Donation matching and paid volunteer hours, including company-funded service trips.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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