[Remote] Senior Data Engineering Manager

Note: The job is a remote job and is open to candidates in USA. YipitData is a leading market research and analytics firm focused on the disruptive economy. They are seeking a Senior Data Engineering Manager to lead the data engineering team for their Public Investor business, responsible for developing engineers and overseeing the architecture of critical data systems that support investment research products.

Responsibilities

• Lead, coach, and develop a global team of data engineers while staying close to architecture, design, code reviews, debugging, and delivery
• Partner with Product Managers, Application Team, and Research Analysts to translate roadmap priorities, customer needs, and research requirements into scalable technical plans
• Build and improve scalable data pipelines, data models, QA systems, and customer-facing delivery mechanisms for Public Investor data products
• Collaborate with Central Team, Feed Operations, Product Specialists, Client Success, and GTM teams to support reliable delivery, incident resolution, client communication workflows, and operational improvements
• Use AI coding tools to 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

Skills

• 8+ years of professional experience in data engineering, data architecture, big data development, ETL engineering, or related technical roles
• 2+ 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
• 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
• 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 customer-facing data feeds, including APIs, flat files, cloud storage, portal-based delivery, or recurring feed delivery systems
• Experience building data pipelines that support AI agents, LLMs, automated insight generation, or AI-powered analytical workflows

Benefits

• Variable target bonus of 10%
• Equity
• Flexible work hours
• Flexible vacation
• A generous 401K match
• Parental leave
• Team events
• Wellness budget
• Learning reimbursement

Company Overview