Senior Data Engineering Manager

YipitData

Senior Data Engineering Manager at YipitData leading a global team and building critical data systems. Focusing on data architecture, AI tools, and production-grade assets for business impact.

Posted 7/23/2026full-timeRemote • New York • 🇺🇸 United StatesSenior💰 $215,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in data engineering and architecture, with a strong focus on building scalable data pipelines and systems. Proven ability to lead and mentor technical teams while collaborating effectively with cross-functional stakeholders.

Highest-signal resume keywords

Data EngineeringData ArchitectureSQLPySparkDatabricks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingETL EngineeringBig Data DevelopmentPipeline ArchitectureData QualityObservabilityProduction ReliabilityWorkflow OrchestrationAI ToolingIncident Resolution

Soft Skills

Team LeadershipMentoringCommunicationCross-Functional CollaborationProblem-Solving

Tools & Technologies

AirflowData PipelinesData ModelsQA SystemsTechnical Exploration

Industry Keywords

OLTPOLAPData ProductsCustomer-Facing DataOperational Improvements

Tech Stack

Tools & technologies

AirflowETLPySparkSQL

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

Flexible work hours
Flexible vacation
Generous 401K match
Parental leave
Team events
Wellness budget
Learning reimbursement
Equity