22 days ago
Base Salary
$260k - $274k/yr
Responsibilities
- Set and evolve the technical direction of the data platform across streaming, batch processing, warehousing, orchestration, governance, and machine learning enablement.
- Lead complex cross-team initiatives from architectural decisions through implementation.
- Design and build real-time pipelines, shared tooling, reusable frameworks, and scalable data infrastructure.
- Establish engineering patterns and golden paths that improve security, consistency, and delivery efficiency.
- Improve platform reliability, scalability, performance, observability, and cost efficiency.
- Partner with Security, Compliance, Product, and Engineering teams on operational and regulatory requirements.
- Strengthen standards for data modeling, pipeline design, testing, deployment automation, and infrastructure as code.
- Influence technical planning and priorities with engineering managers, product managers, and senior technical leaders.
- Mentor senior engineers through design reviews, code reviews, documentation, and hands-on collaboration.
Requirements
- Significant experience designing and evolving large-scale data platforms and distributed or stream-processing systems.
- Deep knowledge of real-time and event-driven architectures using technologies such as Kafka or Pub/Sub.
- Track record of leading complex technical initiatives across multiple teams or domains.
- Experience building platform capabilities, shared services, and reusable engineering patterns.
- Strong judgment across reliability, scalability, performance, governance, security, and cost management.
- Ability to move between high-level architecture and hands-on implementation.
- Experience influencing engineers and stakeholders on shared standards and long-term priorities.
- Experience mentoring experienced engineers and raising technical capability.
- Strong communication skills with technical and non-technical stakeholders.
- Experience working in a regulated environment or designing systems with strong compliance and auditability requirements.
- Experience with the listed technology stack is helpful, but architectural judgment, systems thinking, and technical leadership are prioritized over expertise in any single tool.
Benefits
- Competitive salary package and equity ownership.
- Pay-for-performance equity bonus and Moonshot award opportunities.
- Employer pension contributions from day one.
- Flexible time off, birthday leave, and enhanced parental leave.
- Fully remote or hybrid working from a nearby Moonbase.
- Commuter benefits, private healthcare, Wellhub wellness membership, and lunch credit on office days.
- Home office setup allowance and remote working allowance.
- Unlimited enterprise access to Claude, ChatGPT, Gemini, and other AI tools.
- Monthly product budget and zero-fee crypto transactions.
- $1,000 annual training budget, structured development opportunities, mentorship, and stretch assignments.
- Regular remote company offsites, hackathons, and location-specific cycle-to-work or EV salary-sacrifice programs.
Tech Stack
Apache AirflowApache BeamApache KafkaGoogle BigQueryGoogle Cloud PlatformKubernetesPythonRedisSQLTerraform
Categories
Data Engineering
