Senior Manager, Data Engineering

Turn/River; San Francisco (CA); Híbrido; USD 228.000 - 238.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary and discretionary 5

Medical, dental, and vision insurance

401K matching

Paid parental leave

Flexible vacation policy

Home Office benefits

Annual Home Office Equipment Reimburse

Commuter benefits

Wellness benefits

Office snacks and team lunches

Descripción de la vacante

Turn/River Capital in San Francisco is seeking a Senior Manager, Data Engineering to design, build, and scale the data infrastructure powering analytics across the portfolio.

Lead the evolution of our data platform, strengthen marketing data pipelines (Ads, GA, HubSpot, Salesforce), and define standards for scalable, AI-ready data across functions. You'll mentor engineers and partner with Marketing, RevOps, and Analytics to drive data-driven outcomes.

Formación

• 5+ years of data or analytics engineering experience with ownership of ELT/ETL systems.
• Deep SQL and Python expertise with hands-on dbt, Fivetran, Airbyte, or Matillion.
• Advanced BigQuery or Snowflake experience and modern cloud architecture.
• Proven ability to design scalable data models and enforce engineering best practices.
• Experience integrating GTM systems (Ads, HubSpot, Salesforce, GA4).
• Strong leadership, mentoring, and cross-functional collaboration.
• Bachelor’s degree in a quantitative field or equivalent experience.

Responsabilidades

• Data Platform Ownership: design, maintain, and scale the portfolio’s data platform and ETL/ELT pipelines.
• Marketing Data Integration: unify GTM systems into reliable revenue-linked funnel models.
• Data Architecture & Modeling: build standardized schemas and dbt packages.
• Quality & Governance: implement CI/CD, data validation, and tagging standards.
• AI Workflows: design LLM-powered workflows for content generation and optimization.
• Team Leadership: mentor engineers and lead knowledge sharing.
• Platform Roadmap: plan 12–24 month roadmap toward near-real-time flows and modular reuse.
• Cross-Functional Collaboration: translate data into actionable insights.

Conocimientos

SQL

Python

GTM systems

Leadership

Communication

CI/CD

Educación

Bachelor's degree in a quantitative field

Herramientas

dbt

Fivetran

Airbyte

Matillion

BigQuery

Snowflake

Descripción del empleo

About Turn/River

Turn/River Capital is a private equity firm that partners with software businesses to drive AI transformation and catalyze capital-efficient growth. As a team of equal parts software operators and investors, we have the people, data-driven playbooks and flexible capital to re-architect engineering, product, go-to-market, talent and resourcing to build enduring value. Founded in 2012 and based in San Francisco, Turn/River has $5.6bn in committed capital and invests globally with a focus on North America and Europe.

About the Role

We’re looking for a Senior Manager, Data Engineering to design, build, and scale the data infrastructure that powers analytics across Turn/River’s portfolio.

You’ll lead the evolution of our data platform, ensuring our systems are connected, reliable, and ready for AI-driven insight generation.

Your near‑term focus will be strengthening marketing data pipelines (Ads, GA, HubSpot, Salesforce), while your long‑term remit spans the entire data org: defining standards, improving scalability, and enabling data‑driven execution across all functions.

This role is highly collaborative within Turn/River and across our portfolio companies. You’ll partner closely with Marketing, RevOps, and Analytics leaders to build a unified, AI‑ready data foundation that supports marketing analytics today and scales to all go‑to‑market functions over time.

Key Responsibilities

• Data Platform Ownership: Lead the design, maintenance, and scalability of the portfolio’s BigQuery data platform and ETL/ELT pipelines.

• Marketing Data Integration: Partner with Marketing, RevOps, and Analytics Leads to unify GTM systems (Ads, GA, HubSpot, Salesforce) into reliable revenue‑linked funnel models.

• Data Architecture & Modeling: Build standardized schemas and dbt packages to support analytics consistency across dozens of companies.

• Quality & Governance: Implement CI/CD, data validation, and tagging standards that ensure accuracy and trust.

• AI Workflows: Design and implement LLM-powered workflows (prompt engineering, RAG, agent‑based automation) to streamline content generation, campaign optimization, and performance analysis.

• Team Leadership: Mentor junior data engineers and analysts, foster engineering best practices, and lead knowledge‑sharing across the portfolio.

• Platform Roadmap: Define and execute a 12–24-month roadmap evolving the platform toward near‑real‑time flows, identity resolution, and modular reuse.

• Cross‑Functional Collaboration: Partner with Analytics and Systems teams to turn fragmented data into actionable insight and scalable automation.

Qualifications

• 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 (preferred) or Snowflake and modern cloud‑based architecture.

• Proven ability to design scalable data models and enforce engineering best practices, including Git‑based workflows and CI/CD automation.

• Experience integrating GTM systems (Ads, HubSpot, Salesforce, GA4) and building reliable revenue‑linked pipelines.

• Demonstrated success leading complex data projects and mentoring technical contributors.

• Exceptional communicator who can bridge technical detail with business context and cross‑functional impact.

• Bachelor’s degree in a quantitative field (Computer Science, Engineering, Statistics, Mathematics, or Business Analytics) or equivalent professional experience.

• Intellectually curious, systems‑minded, and detail‑obsessed — passionate about building scalable, reusable, and future‑proof data infrastructure that drives portfolio growth.

Location

• San Francisco, hybrid work model.

Compensation

• The annual base salary range for this role is $227,500 - $237,500, taking into account numerous variable factors that are considered in making compensation decisions including but not limited to skill sets, experience, training, licensure, certifications, and organizational requirements.

Benefits and Perks

The below benefits are offered to full‑time employees based out of our San Francisco office:

• An opportunity to make an impact across multiple high‑growth tech firms

• Competitive salary and discretionary bonus

• Medical, dental, and vision insurance covered 100% for employee & dependents

• Flexible vacation policy

• 401K 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 Monday & Friday

• Energetic work environment with snacks and weekly team lunches 3x per week, centrally located near multiple public transit lines

• A company that enjoys having fun: holiday parties, annual company offsite and retreat, annual summer "work from anywhere" month

Turn/River provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, religious creed (including religious dress and grooming practices), national origin, ancestry, citizenship, physical or mental disability, medical condition (including cancer and genetic characteristics), genetic information, marital status, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender, gender identity, gender expression, natural hair styles, age (40 years and over), sexual orientation, veteran and/or military status, protected medical leaves (requesting or approved for leave under any applicable state, or federal leave act), domestic violence victim status, political affiliation, and any other characteristic or status protected by state or federal law.