Senior Manager, Data Engineering

Turn/River•San Francisco, CA

2d•$227,500 - $237,500•Hybrid

About The Position

Turn/River Capital is a private equity firm that partners with software businesses to drive AI transformation and capital-efficient growth. Founded in 2012 and based in San Francisco, the firm has $5.6 billion in committed capital and invests globally, with a focus on North America and Europe. The Senior Manager, Data Engineering will design, build, and scale data infrastructure that powers analytics across Turn/River’s portfolio. The role leads the evolution of the data platform, ensuring systems are connected, reliable, and ready to support AI-driven insight generation. Near-term priorities include strengthening marketing data pipelines across Ads, Google Analytics, HubSpot, and Salesforce. The broader remit includes defining data standards, improving scalability, and enabling data-driven execution across functions. The role works collaboratively within Turn/River and across portfolio companies, partnering with Marketing, RevOps, Analytics, and Systems leaders to create a unified, AI-ready data foundation. The position is based in San Francisco with a hybrid work model.

Requirements

At least 5 years of data or analytics engineering experience, including ownership of production-grade ELT/ETL systems.
Deep expertise in SQL and Python, with hands-on experience using dbt, Fivetran, Airbyte, or Matillion.
Advanced proficiency in BigQuery or Snowflake and modern cloud-based architecture; BigQuery is preferred.
Experience designing scalable data models and enforcing engineering best practices, including Git-based workflows and CI/CD automation.
Experience integrating go-to-market systems such as Ads, HubSpot, Salesforce, and GA4, and building reliable revenue-linked pipelines.
Demonstrated success leading complex data projects and mentoring technical contributors.
Exceptional communication skills, with the ability to connect technical detail to business context and cross-functional impact.
Bachelor’s degree in a quantitative field such as Computer Science, Engineering, Statistics, Mathematics, or Business Analytics, or equivalent professional experience.
Intellectual curiosity, a systems mindset, attention to detail, and passion for building scalable, reusable, future-proof data infrastructure that drives portfolio growth.

Responsibilities

Lead the design, maintenance, and scalability of the portfolio’s BigQuery data platform and ETL/ELT pipelines.
Partner with Marketing, RevOps, and Analytics leads to integrate Ads, Google Analytics, HubSpot, and Salesforce into reliable, revenue-linked funnel models.
Build standardized schemas and dbt packages to support consistent analytics across dozens of companies.
Implement CI/CD, data validation, and tagging standards to ensure data accuracy and trust.
Design and implement LLM-powered workflows, including prompt engineering, retrieval-augmented generation (RAG), and agent-based automation, to streamline content generation, campaign optimization, and performance analysis.
Mentor junior data engineers and analysts, foster engineering best practices, and lead knowledge-sharing across the portfolio.
Define and execute a 12–24-month platform roadmap, evolving toward near-real-time data flows, identity resolution, and modular reuse.
Partner with Analytics and Systems teams to turn fragmented data into actionable insight and scalable automation.

Benefits

Competitive salary and discretionary bonus.
Medical, dental, and vision insurance covered 100% for the employee and dependents.
Flexible vacation policy.
401(k) matching.
Paid parental leave.
Commuter benefits.
Health and wellness benefits.
Household services benefits.
Home office benefits.
Annual home office equipment reimbursement.
Donation matching.
Work from home on Mondays and Fridays.
Snacks and weekly team lunches three times per week.
Holiday parties, an annual company offsite and retreat, and an annual summer work-from-anywhere month.
Opportunity to make an impact across multiple high-growth technology firms.