Lead the evolution of a critical data platform by managing the design and performance of end-to-end data systems that power deep insights across a growing vendor ecosystem. In this role, you'll combine technical depth with leadership to shape architecture, improve reliability, and scale data infrastructure using modern tools and practices.
What You’ll Do
- Design, implement, and refine scalable data pipelines that support complex analytical workloads and real-time decision-making.
- Set standards for data modeling, pipeline orchestration, and system resilience across distributed environments.
- Partner with product and engineering teams to turn business requirements into efficient, maintainable data solutions.
- Use Databricks and Airflow daily to process and orchestrate large volumes of data, with exposure to Dagster and dbt for advanced workflows.
- Diagnose and resolve performance bottlenecks and system failures to ensure uptime and accuracy.
- Guide engineers through technical challenges, code quality, and architectural decisions, fostering a culture of growth and ownership.
- Help define long-term technical direction, focusing on efficiency, scalability, and innovation in data processing.
What We’re Looking For
- At least six years of hands-on experience in data engineering, data architecture, or related technical fields.
- Two or more years leading technical teams, including mentorship, performance feedback, and project oversight.
- Deep proficiency in SQL, PySpark, and distributed data systems, with proven experience scaling data workloads in production.
- Real-world experience with Airflow for orchestrating complex workflows; familiarity with Dagster or dbt is a plus.
- Ability to operate independently in fast-moving environments while delivering reliable results under deadlines.
- Strong communication skills to collaborate effectively with both technical and non-technical partners.
- Experience translating business problems into scalable data architectures.
Nice to Have
- Exposure to AI/ML pipelines, vector search, or Elasticsearch for enriching data workflows.
- Familiarity with Django or similar frameworks for integrating data into applications.
- Track record of building robust, automated data systems in agile settings.
- Ability to deliver high-quality work on tight timelines without sacrificing maintainability.
Technology Environment
Databricks, Airflow, PySpark, SQL, Elasticsearch, Dagster, dbt, Django
Work Environment
This is a hybrid role with team hubs in NYC, Austin, Miami, Denver, and Mountain View. Remote work is supported across the U.S., though assignments outside office locations may be subject to New York State tax withholding. The team values flexibility, ownership, and purposeful progress.
Benefits & Compensation
- Competitive base salary ranging from $190,000 to $230,000
- Equity participation and variable compensation potential up to 15%
- Flexible hours and vacation policy
- Generous 401K matching, parental leave, and wellness benefits
- Learning reimbursement and team-wide development opportunities
- Comprehensive medical, dental, and retirement coverage
Our Culture
We believe in transparency, merit, and continuous growth. Team members are trusted to own outcomes, move with purpose, and contribute meaningfully. Titles matter less than impact. We foster an environment where curiosity, accountability, and collaboration drive results.
Equal Opportunity
We welcome diversity in all forms and are committed to building an inclusive workplace. Employment decisions are based on merit, experience, and potential—not race, religion, gender identity, sexual orientation, age, disability, veteran status, or any other protected characteristic. We are proud to be an equal opportunity employer.
