Senior Data Platform Engineer

We are looking for a Senior Data Platform Engineer to help us build the next generation of our data platform, a streaming-first, domain-oriented foundation designed for speed, ownership, and trust. You will work on the infrastructure, tooling, and paved paths that allow data to flow from production systems into a governed medallion architecture, enabling near real-time access for analysts, engineers, AI systems, and business users across the organization.

This is a high-impact role at the center of a platform transformation: enabling self-serve data access, moving towards near real time data access, and establishing data as a first-class product surface owned at the source.

How we’re using AI today

Our Engineering, Product, and Design teams are thoughtfully integrating AI across the full software and product development lifecycle to move faster without sacrificing quality or security. In practice, that looks like engineers using AI-assisted coding tools to accelerate reviews and catch bugs earlier, product managers synthesizing user research at scale, and designers rapidly prototyping and iterating with AI-generated mockups. We approach AI the same way we approach security: with clear principles, human accountability at every consequential decision point, and rigorous evaluation before anything ships to customers.

This is a remote opportunity within the US.

What we're looking for:

• You have a passion for designing, implementing, and operating stable, scalable, and efficient data systems
• Deep experience with streaming architectures and event-driven data pipelines
• Strong focus on schema governance, data quality, and data lifecycle management
• Proven track record of architecting, building, deploying, and supporting scalable production systems across 7+ years of experience
• Enjoys leading through individual technical contribution while mentoring and supporting the growth of other data platform engineers
• Strong commitment to software engineering and data infrastructure best practices
• Curiosity and interest in emerging AI technologies and applications
• Prefer BS, MS, or Ph. D. in Computer Science with 7+ years of proven relevant industry experience
• 5+ years experience working on Cloud Platforms (AWS primarily or GCP) and open-source technologies supporting data infrastructure, platforms & tools
• 5+ years experience with Big Data query engines & data stores such as Databricks, Snowflake, Redshift, etc.
• Great communication skills capable of working cross functionally with different teams in Engineering and prioritizing critical needs for Data Platform
• Experience programming, building and deploying products that rely on large-scale distributed systems in Python, Go, Scala/Java, or other similar languages
• 5+ years experience with large-scale, distributed systems design and development with an understanding of scaling, replication, consistency, and high availability
• 5+ years experience with Infrastructure as Code (IaC) tools like Terraform or Ansible.
• Experience with compute layer like EC2, ECS, EKS or similar

Bonus points for:

• Implementing secure systems/datastores with least privilege access (e.g. IAM) and encryption
• Experience using streaming technologies like Apache Kafka, Kinesis, Flink, etc.
• Implementing quality monitoring/alerting using tools like Prometheus, Grafana or Datadog
• Experience with Dagster or other orchestration tooling
• Experience with data modelling tooling such as dbt

What you can expect:

• Design, implement, and maintain a streaming-first data platform built on Apache Kafka, Protobuf, and Apache Iceberg, enabling near real-time data availability across the organization
• Build and operate a hybrid Databricks and Snowflake architecture: leveraging Databricks for data engineering, streaming processing, and AI/ML workloads, and Snowflake as the governed serving layer for analytics and business reporting
• Own the unified storage layer to ensure all consumers operate on a consistent and governed data foundation
• Champion platform standards, tooling, and best practices across the data organization

Successful applicants will be required to complete a background check that may consist of prior employment verification, reference checks, education confirmation, criminal background, publicly available social media, credit history, or other information, as permitted by local law.