Job Description
The role involves leading the evolution of large-scale data platform systems at Amperity, focusing on unifying batch and real-time processing, managing complex codebases, and applying AI tooling to enhance data infrastructure and customer experience.
Key Responsibilities
- Unify batch and real-time event processing across core platform services.
- Manage and evolve a large, mature codebase, including technical debt prioritization.
- Translate customer requirements into high-value engineering work.
- Build seamless integrations with data platforms and cloud infrastructure.
- Establish norms for AI tooling usage to accelerate development and ensure validation.
- Assess and improve complex, high-scale software systems, including platform migrations and architectural transitions.
- Identify and address technical debt, balancing maintenance and innovation.
- Collaborate with product teams to translate roadmap plans into technical solutions.
Requirements
- Nine (9) years of experience building and evolving complex, high-scale software systems.
- Experience leading platform migrations or major architectural transitions.
- Experience with streaming data processing is a strong plus.
- Ability to operate in a complex, high-ownership environment and assess systems honestly to identify bottlenecks and build credible paths forward.
- Fluent in the capabilities of AI tooling, with the ability to balance its limitations.
- Experience in shipping high-quality work, iterating based on evidence, and making confident decisions through ambiguity.
- Comfortable inheriting large, imperfect codebases, reading technical debt, communicating it with partners, and making principled decisions about when to sustain or address it.
- Customer-first thinking, starting with the value delivered and shaping work scope and sequence accordingly.
- Technical depth in distributed systems, data-intensive architectures, or cloud-native infrastructure.
- Partnering effectively with Product teams to translate engineering realities into clear options, advocating for the right technical investments, and shaping forward-looking plans.
- Experience with large-scale data engines such as Apache Spark, Presto, and Kafka.
- Experience with infrastructure built with Kubernetes and Terraform, deployed across AWS and Azure.
- Experience with native integrations with customer data platforms including Snowflake and Databricks, supporting bring-your-own-storage architectures.
Benefits & Perks
Base salary range of $190,000 to $260,000, depending on skills, experience, education, training, location, and level
Cash incentives
Stock options with equity grants
Hybrid work model with three days in the office each week
100% employee healthcare coverage
Transportation subsidies
Work environment with snacks and employee experience perks such as events and activities (both in-person and remote)
Self-managed paid time off (PTO)
Flexible work arrangements
Inclusive environment supporting full potential and diversity
Ready to Apply?
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