Data Engineering Manager

 

About Us:

YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments.

Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to rigorous analysis and expert narrative framing, our teams ensure clients get not just data, but clarity and confidence.

We operate globally with offices in the US (NYC, Austin, Miami, Mountain View), APAC (Hong Kong, Shanghai, Beijing, Guangzhou, Singapore), and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery.

What It’s Like to Work at YipitData:

YipitData isn’t a place for coasting—it’s a launchpad for ambitious, impact-driven professionals.

From day one, you’ll take the lead on meaningful work, accelerate your growth, and gain exposure that shapes careers.

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

If your ambition is matched by your work ethic—and you're hungry for a place where growth, impact, and ownership are the norm—YipitData might be the opportunity you’ve been waiting for.

About The Role:

We are looking for a highly skilled Data Engineering Manager to join our Data Engineering team and play a central role in building and scaling our vendor universe—the database of companies we track and analyze. Reporting directly to the Senior Director of Data Engineering, this role demands technical leadership, independence, and the ability to deliver under tight deadlines in a fast-paced environment.

As a Data Engineering Manager, you will design and maintain large-scale data pipelines, define best practices for ETL, and integrate emerging technologies to keep our platform on the cutting edge. You’ll work cross-functionally to deliver reliable, efficient, and scalable data solutions while contributing hands-on expertise in Databricks, Airflow, PySpark, and SQL.

What You’ll Do

• Own the design, build, and optimization of end-to-end data pipelines that power our vendor universe.
• Establish and enforce best practices in data modeling, orchestration, and system reliability.
• Collaborate with product, engineering, and business stakeholders to translate requirements into robust, scalable data solutions.
• Work extensively with Databricks and Airflow for large-scale data processing and orchestration.
• Troubleshoot and resolve complex pipeline issues to ensure reliability and performance.
• Contribute to the team’s technical strategy, helping drive improvements in scalability, performance, and efficiency.
• Lead, mentor, and support engineers through challenges, code reviews, and project execution.

What We’re Looking For

• 6+ years of professional experience in Data Engineering or equivalent technical roles (e.g., data architecture, big data development, or ETL engineering).
• 2+ years of managerial experience, including mentoring, team leadership, and supporting delivery.
• Strong expertise in SQL and distributed data systems.
• Proficiency with PySpark and Databricks for processing and scaling large datasets.
• Hands-on experience with Airflow for pipeline orchestration (Dagster/dbt a plus).
• Proven track record of delivering in fast-paced, deadline-driven environments with minimal oversight.
• Strong problem-solving skills and ability to translate business needs into scalable technical solutions.
• Excellent communication and collaboration skills with both technical and non-technical stakeholders.

Nice to Have

<