Note: The job is a remote job and is open to candidates in USA. YipitData is the leading market research and analytics firm for the disruptive economy, seeking a highly skilled Senior Data Engineering Manager to lead their data engineering teams. The role involves developing engineers, guiding technical architecture, and owning critical data pipelines that support products and customer-facing data feeds.
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
Skills
- 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
- Experience working with application teams with OLTP and OLAP use cases
- 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 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
Benefits
- Flexible work hours
- Flexible vacation
- A generous 401K match
- Parental leave
- Team events
- Wellness budget
- Learning reimbursement
- This role may be performed fully remotely within the United States.
Company Overview