About the Role
The company is building a robust data platform essential for our innovative products, including robots, live spatial intelligence, and real-time AI solutions. As a Senior Data Engineer, you will play a crucial role in shaping this platform. You will not simply maintain an existing architecture; instead, you'll be instrumental in building the foundation on which the company's operations depend.
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What We're Looking For
We are in need of an experienced backend engineer who has navigated high-scale systems, focusing not merely on isolated data pipelines but on understanding the demands placed on systems under real-world loads. As we advance our product offerings and generate real-time data, we need a senior-level professional capable of creating a resilient data platform.
Key Responsibilities
- Design and build the core data infrastructure that supports the company's products, including data ingestion, transformation, storage, and pipeline connections.
- Make significant architectural decisions regarding data handling at scale, rather than solely following existing specifications.
- Focus on reliability and performance from the outset, as the platform will serve live products with real user interactions and partnerships.
- Collaborate directly with engineers working on Hive, RaaS, and other product lines to accurately address their data layer needs, creating solutions alongside them.
What Makes This Role Unique
In this position, you will not be burdened by legacy systems or complex organizational hierarchies. Our engineering culture is flat, allowing for streamlined decision-making without the constraints of tech leads or middle management. You have the autonomy to implement your vision for the platform without having to navigate through multiple layers of approval. Instead of working with abstract data, you will engage with information sourced from physical robots, live venues, and real-time athlete performance.
Skills Required
- Extensive backend engineering experience in high-scale production systems, beyond just analytics or reporting pipelines.
- Proven hands-on experience with distributed data processing tools (e.g., Spark) and workflow orchestration (e.g., Airflow).
- Practical experience in designing data architecture from the ground up, including schema design, storage trade-offs, and large-scale ingestion processes.
- A strong foundation in cloud data infrastructure (AWS or GCP) along with expertise in operational aspects such as cost efficiency, performance, and reliability.
- Ability to manage ambiguity since this is an early-stage platform that does not come with a predefined playbook.
Nice to Have
- Familiarity with modern lakehouse tools (e.g., dbt, Iceberg) or experience with real-time/streaming data.
What We're Not Looking For
This position is not suitable for individuals who prefer a fully defined roadmap or require multiple processes and approvals to proceed. If you aspire to construct data infrastructure for tangible, real-world systems and feel confident making impactful decisions, this role is for you. Conversely, if maintaining existing systems is your preference, this role may not align with your goals.
