YipitData
Senior Data Engineering Manager
Vaga remota de Data Engineering Manager com fit claro de localização do candidato.
Publicada4 de jul. de 2026
Países elegíveis20 países aceitos
Sinal de senioridadeLead
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Resumo da vaga
Senior Data Engineering Manager
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
Why Top Talent Chooses YipitData:
- Ownership That Matters: You’ll lead high-impact projects with real business outcomes
- Rapid Growth: We compress years of learning into months
- Merit Over Titles: Trust and responsibility are earned through execution, not tenure
- Velocity with Purpose: We move fast, support each other, and aim high—always with purpose and intention
What You’ll Own
- Large scale data pipelines built for the investor team supporting applications, feeds, and insight agents.
- Production datasets and analytical models used in research workflows, internal products, and customer-facing deliverables.
- Customer-facing data feeds and recurring external data deliveries with strong expectations around accuracy, timeliness, and reliability.
- AI-ready analytical datasets designed with the structure, metadata, documentation, and business context needed for effective use by AI agents and insight-driven applications.
- Data quality and observability frameworks, including validation checks, freshness monitoring, coverage monitoring, outlier detection, and automated QA controls.
- Technical execution across Databricks, Airflow, SQL, PySpark, and related data infrastructure.
- Operational excellence practices across documentation, incident response, monitoring, reliability, and production support.
What You’ll Do
- 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.
What We’re Looking For
- 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.
Nice to haves
- 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.
What We Offer:
- We care about your personal life, and we mean it. We offer flexible work hours, flexible vacation, a generous 401K match, parental leave, team events, wellness budget, learning reimbursement, and more!
- Your growth at YipitData is determined by the impact that you are making, not by tenure, unnecessary facetime, or office politics. Everyone at YipitData is empowered to learn, self-improve, and master their skills in an environment focused on ownership, respect, and trust. See more on our high-impact, high-opportunity work environment above!
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