Engineering Manager, Data Platform
@ FloQastEngineering Manager, Data Platform
About the job
FloQast is an AI-powered accounting platform automating workflows for over 3,500 clients. This role combines technical expertise with team leadership on data infrastructure.
Requirements
- 12+ years in data infrastructure
- Hands-on Spark experience
- Familiar with lakehouse stack
- Management or lead experience
- Strong communicator skills
Qualifications
- Bachelor's degree preferred
- Experience in high-growth SaaS
- Knowledge of AI/ML pipelines
- Creative problem solver
- Team leadership skills
Full job description
As Engineering Manager for the Data Platform team, you'll lead a team of engineers building and operating the infrastructure that powers data ingestion, governance, storage, processing, and access across FloQast's product and analytics systems. This is a deeply technical role — roughly half your time is writing code, designing systems, and making architecture calls alongside your team. The other half is growing the people doing that work: hiring, developing, unblocking, and setting direction.
You've spent years in data infrastructure and you still love the work. You can reason through a Spark shuffle problem, pick apart a slow Iceberg compaction job, and make a principled call between PySpark and Scala Spark on a real workload. You've run Structured Streaming pipelines, operated Kafka at scale, and debugged the Spark UI until the stage times made sense. But you've also learned that technical impact compounds through people — that the systems you architect matter less than the engineers you develop. You've managed before, or you've been the informal lead that everyone went to, and you're ready to own it fully.
At FloQast, you'll apply that combination 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. The platform serves 30,000+ tenants. You'll hold technical authority on data compute and architecture decisions while building the team that executes them — and you'll do both at the same time, not in phases.
What You'll Do
As a technical contributor (≈50%)
As a team lead (≈50%)
What You'll Bring
- 12+ years of software engineering experience in data infrastructure, distributed systems, or backend platform engineering
- Hands-on production experience with Spark — you can tune jobs, understand the Catalyst optimizer, and have strong opinions on PySpark vs. Scala Spark
- Familiarity with the modern lakehouse stack: Iceberg, Kafka/MSK, Airflow/MWAA, Trino or Athena, and cloud-native AWS services
- Experience with Snowflake, dbt, and building data access APIs or platform tooling
- 2+ years of engineering management or formal tech lead experience — you've done performance reviews, owned a hiring loop, or led a team through a significant technical program
- Comfort holding both hats: you can spend a morning in code review and an afternoon in a difficult growth conversation, and you're good at both
- Strong communicator who can make technical trade-offs legible to product and business stakeholders
- Experience in a startup or high-growth SaaS environment
- Exposure to AI/ML data pipelines or real-time analytics is a plus
Here’s Why You Should Apply
- What is engineering working on? Our FQ Engineering Blog showcases a number of our recent efforts straight from the engineers working on them. Check it out!Similar jobs in Columbus, OH
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