Senior Data Engineering Manager

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.