hirly

FloQast

Senior Staff Engineer, Data

San Jose, California

See how you match this job — and similar ones. Free.

Upload your resume and hirly scores it against this role at FloQast first, then against similar open jobs, and shows where you fit and why.

PDF or DOCX, up to 12MB. No sign-up to see your matches.

Get past the screening software and onto a recruiter's desk

hirly rewrites your resume for this job — matching the keywords and skills in the posting, moving your most relevant experience to the top, and writing a cover letter to fit. About 30 seconds.

  • Keywords matched to this posting
  • Fit score before you apply
  • Cover letter included

Matched against 2.4M live jobs from 200,000+ employers in 200+ countries.

Tailor my resume for this job →

Apply from your AI assistant

Connect hirly to Claude and ask it to apply to this job. hirly tailors your resume, fills the employer’s form and asks before sending. ChatGPT: manual setup today.

Some employer sites stop an application at a CAPTCHA or sign-in and hand it back with a link. Applying needs a paid plan. Works with any assistant that supports MCP.

hirly's read of this role

Role family
Engineering
Seniority
Lead / management
Country
US
Work mode
On-site / unstated
First seen by hirly
2 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

As a Senior Staff Engineer, Data, you'll be a key technical leader driving the design, implementation, and evolution of FloQast's core data platform. You will define the standards and patterns that power data ingestion, governance, storage, processing, and access across all product and analytics systems — with Apache Spark as the primary compute engine at the heart of that stack. Your work will enable teams across engineering, product, and business operations to build on a reliable, scalable, and secure data foundation.

You've spent years going deep on Spark in production. You reason through shuffle behavior, partition strategies, and memory pressure without reaching for documentation. You understand what the Catalyst optimizer does with your query plan and you write code that helps it. You've made the call between PySpark and Scala Spark on real workloads, run Structured Streaming pipelines over Kafka topics on MSK, and debugged slow stages in the Spark UI. You've built Spark jobs that read and write Apache Iceberg tables at scale — managing snapshot isolation, schema evolution, and compaction as operational concerns, not afterthoughts. At this level, you don't just tune pipelines. You set the architecture that determines whether the next order of magnitude is a rewrite or a config change.

At FloQast, you'll apply that depth across our full lakehouse stack. FloLake runs on Iceberg over S3, orchestrated through MWAA, cataloged in AWS Glue, and queried via Trino and Athena. Kafka on MSK moves data through the hot path. You'll own the compute architecture decisions that 30,000+ tenants depend on, define how Spark jobs are structured and governed across the platform, and set the bar for how the team thinks about distributed systems. Engineers at all levels will look to you as the authority on what good looks like — and you'll build the systems that prove it.

Original posting on FloQast's site ↗

Browse similar roles

Want this one?

Upload your resume and hirly rewrites it for this job and writes the cover letter — in about thirty seconds, before you sign up.

Tailor my resume for this job