Lead and shape the future of data infrastructure for a growing technology company focused on intelligent decisioning systems. As Engineering Manager of the Data Platform team, you'll guide the design and evolution of systems that process, store, and serve critical data at scale—supporting both product features and advanced data science workflows.
What You’ll Do
- Manage and develop a team of data engineers, fostering growth, technical excellence, and ownership
- Define the long-term vision for data pipelines, storage, and access patterns across batch and streaming workloads
- Build and maintain robust, observable data systems that ensure reliability, quality, and performance
- Collaborate with Data Science to streamline access to clean, well-modeled data for modeling and analysis
- Work alongside Product and Engineering to enable data-rich features and real-time decisioning capabilities
- Partner with Infrastructure teams to optimize cost, scalability, and operational efficiency
- Establish standards for data governance, schema evolution, and pipeline resilience
- Drive incident response, monitoring, and operational best practices for data services
- Contribute to architectural design and solve complex technical challenges as needed
- Recruit and onboard new engineering talent, maintaining a high standard for technical and cultural fit
What We’re Looking For
- 2–5+ years of experience managing engineering teams focused on data or platform infrastructure
- Proven background as a senior data or backend engineer with deep experience in data systems
- Hands-on expertise in building scalable ETL/ELT pipelines and distributed data architectures
- Proficiency in Python, Golang, or similar programming languages
- Familiarity with cloud data platforms on AWS, GCP, or Azure
- Solid understanding of databases, data modeling, and query optimization using SQL and data warehouses
- Experience delivering production-grade data systems in fast-moving environments
- Ability to lead technical discussions and engage deeply in system design
Nice to Have
- Experience with Spark, Kafka, Flink, or other big data and streaming technologies
- Familiarity with data lakes, Redshift, and modern data stack patterns
- Background in building data platforms for machine learning or fraud detection systems
- Domain knowledge in fintech or risk analytics
Technology Environment
Our stack includes Golang, Python, PostgreSQL (RDS), Redshift, EMR, Spark, Docker, OpenSearch, AWS Lambda, AWS Cognito, and core AWS services. You’ll work in a hybrid environment with team members across Austin, San Francisco, New York, Seattle, Los Angeles, Chicago, Gurugram, and Bengaluru, with flexibility for remote work within the U.S.
Compensation & Benefits
- Competitive salary range: $200,000–$240,000 per year
- Equity participation
- Employer-paid health insurance for you and your dependents
- 401(k) with employer match (or equivalent outside the U.S.)
- Flexible paid time off
- Home office stipend
- Regular in-person company gatherings
