Senior Data Engineering Manager

YipitData

16h•Remote

About The Position

YipitData is seeking a highly skilled Senior Data Engineering Manager to lead one of its data engineering teams. This is a hands-on player-coach role focused on developing engineers, guiding technical architecture, and contributing directly to systems supporting products, AI platforms, and customer-facing data feeds. The role involves owning critical central data pipelines built on large-scale alternative datasets, transforming complex data into reliable, production-grade assets for various internal and external users. The ideal candidate combines strong technical judgment, operational rigor, people leadership, and modern AI-assisted development practices, utilizing tools like Claude Code, Codex, or Cursor to enhance efficiency while maintaining high standards.

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.
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.

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 internal business stakeholders, including collaboration with leadership to align on strategic initiatives.
Experience building data pipelines that support AI agents, LLMs, automated insight generation, or AI-powered analytical workflows.

Responsibilities

Lead the data engineering team responsible for building and scaling data systems for all of YipitData’s businesses.
Own large-scale data pipelines for public investor, corporate investor, and/or private investor business units.
Manage production datasets and analytical models used in research workflows, applications, internal products, and customer-facing deliverables.
Architect data flows and data models to support various business stakeholders' use cases, focusing on accuracy, timeliness, and reliability.
Develop AI-ready analytical datasets with appropriate structure, metadata, documentation, and business context for AI agents.
Implement and manage data quality and observability frameworks, including validation checks, freshness monitoring, coverage monitoring, outlier detection, and automated QA controls.
Drive technical execution across Databricks, Airflow, SQL, PySpark, and related data infrastructure.
Ensure operational excellence practices across documentation, incident response, monitoring, reliability, and production support.