Sr Staff - Data Platform Engineer

New

USFull-TimeStaff

Salary220,000 USD to 255,800 USD annually

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Job Details

15+ years of software engineering experience with strong focus on distributed systems and platform engineering.
At least 4+ years in Staff or Principal-level engineering roles leading large-scale platform initiatives.
Strong computer science fundamentals including system design, algorithms, and data structures.
Advanced software engineering experience in Java (Spring Boot, microservices) and Python, with emphasis on production-grade systems.
Proven experience building data platforms, APIs, or frameworks—not limited to ETL or dashboard development.
Deep expertise in data lakehouse technologies such as Apache Iceberg, Hudi, or Delta Lake.
Experience with large-scale distributed data processing frameworks such as Spark or similar open-source ecosystems.
Strong background in cloud infrastructure (AWS or Azure), including services like S3, EMR, Kubernetes, and Lambda.
Hands-on experience with CI/CD, Terraform, Git-based workflows, and modern DevOps practices.
Exposure to AI-native development workflows, including LLM-assisted engineering and automation of SDLC tasks.
Proven ability to lead through influence across multiple engineering teams and organizational boundaries.
Strong communication skills with ability to explain complex architectural trade-offs to both executives and engineers.

Define and own the long-term architectural vision and 3–5 year roadmap for the enterprise data platform and lakehouse ecosystem.
Design and build platform-as-a-product capabilities, including internal SDKs, APIs, CLI tools, and orchestration frameworks.
Architect scalable data systems that integrate storage, compute, and metadata layers using modern lakehouse technologies.
Develop abstractions and control planes that simplify infrastructure complexity for downstream data and software engineers.
Prototype, evaluate, and integrate emerging technologies to improve performance, scalability, and cost efficiency.
Design and implement governance-by-design systems, including data lineage, security controls, and PII protection mechanisms.
Enable real-time and streaming data ingestion pipelines, including AI and telemetry-driven data sources.
Lead architectural reviews and serve as the escalation point for complex system design and production issues.
Establish engineering best practices and drive code quality, scalability, and system reliability standards across teams.
Mentor engineers and influence the broader data engineering organization, including hiring standards and technical growth paths.

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