# Senior Data Engineering Manager

**Company**: YipitData
**Location**: US Remote
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Salary**: up to $215,000 per year, with a variable target up to 10%
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/yipitdata/jobs/8080900?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_8ce3133e-a80

## Description

We are seeking a highly skilled Senior Data Engineering Manager to lead one of our data engineering teams. This is a hands-on player-coach role for someone who can develop engineers, guide technical architecture, and contribute directly to the systems that support our products, AI platforms, and customer-facing data feeds.

You will own critical central data pipelines built on large-scale alternative datasets, including transaction data, email receipt data, B2B spend data, and other third-party datasets. Your team will transform complex data into reliable, production-grade assets used by research analysts, product teams, and internal applications.

Responsibilities:

- Lead, coach, and develop a global team of data engineers while staying close to architecture, design, code reviews, debugging, and delivery.

- Partner with Technical Product Managers and Data leads to translate roadmap priorities, customer needs, and research requirements into scalable technical plans.

- Build and improve scalable data pipelines, data models, and QA systems for various data products.

- Collaborate with business stakeholders and PMs to support reliable delivery of data pipelines, incident resolution, methodologies, and operational improvements.

- Use AI coding tools to develop and enhance methodologies, accelerate engineering execution, improve documentation, strengthen QA, support technical exploration, and raise team productivity.

- Create clarity and momentum in ambiguous environments by breaking down complex data, research, and product challenges into actionable engineering plans.

Requirements:

- 8+ years of professional experience in data engineering, data architecture, big data development, ETL engineering, or related technical roles.

- 3+ years of managerial experience, including mentoring, team leadership, and supporting delivery.

- Experience managing, mentoring, or formally leading data engineers or technical teams in a hands-on player-coach capacity.

- Strong hands-on expertise with SQL, PySpark, Databricks, and Airflow or similar workflow orchestration tools and AI toolings.

- Experience building, maintaining, or scaling business-critical data systems, including pipelines, production datasets, data delivery systems, or customer-facing data products.

- Deep technical judgment across data modeling, distributed data systems, pipeline architecture, orchestration, data quality, observability, and production reliability.

- Strong communication and cross-functional collaboration skills, especially with Product, Research, Operations, Client Success, Sales, and Engineering stakeholders.

Nice to Have:

- Experience with alternative data or financial data, including consumer transaction data, email receipt data, B2B spend data, or other large-scale third-party datasets.

- Experience supporting internal business stakeholders, including collaboration with leadership to aligned on strategic initiatives.

- Experience building data pipelines that support AI agents, LLMs, automated insight generation, or AI-powered analytical workflows.

What We Offer:

- Competitive salary: up to $215,000 per year, with a variable target up to 10%.

- Comprehensive benefits, perks, and equity.

- Flexible work hours, flexible vacation, a generous 401K match, parental leave, team events, wellness budget, learning reimbursement, and more!

- Opportunity to work remotely within the United States.

## Skills

### Required
- SQL
- PySpark
- Databricks
- Airflow
- data engineering
- data architecture
- big data development
- ETL engineering

### Nice to have
- alternative data
- financial data
- consumer transaction data
- email receipt data
- B2B spend data
- AI agents
- LLMs
- automated insight generation
- AI-powered analytical workflows

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/yipitdata/jobs/8080900?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)