# Senior Staff Engineer, Data

**Company:** [FloQast](https://hotfix.jobs/companies/floqast)
**Location:** San Jose, CA
**Role:** Data Engineering
**Experience:** 7+ years
**Skills:** Spark, apache iceberg, Kafka, Airflow, Snowflake, dbt, AWS, aws s3, aws glue, mwaa, trino, athena, pyspark, Scala, structured streaming
**Posted:** 2025-06-06

> Leads architecture and evolution of a large-scale data platform spanning ingestion, lakehouse storage, streaming, governance, and access. Requires 10+ years of software engineering experience, deep production expertise with Spark and distributed systems, and strong cloud data-platform experience.

## Job Description

## Responsibilities
- Lead the design of scalable and reliable data pipelines, storage solutions, and access layers using modern cloud-native technologies.
- Own and evolve core data platform components, including event streaming, lakehouse architecture, batch and streaming ETL, and data cataloging.
- Define best practices for data quality, lineage, privacy, and access control to ensure regulatory compliance and trust in the data.
- Collaborate with Product, Analytics, Infrastructure, and Security teams to align data platform capabilities with organizational goals.
- Mentor engineers across the organization, establish coding and architectural standards, and influence the strategic direction of the platform.
- Evaluate and integrate technologies that improve performance, observability, developer experience, and cost efficiency.
- Define compute architecture and standards for Spark jobs across the data platform.
- Build and operate production-grade Spark pipelines using Apache Iceberg, Kafka, and cloud-native data services.

## Requirements
- 10+ years of software engineering experience with deep expertise in data infrastructure, distributed systems, or backend platform engineering.
- Proven experience designing and delivering production-grade data platforms at scale, including platforms supporting hundreds of terabytes of data and thousands of jobs per day.
- Strong experience with Snowflake, dbt, Kafka, Airflow, Spark, and cloud-native technologies such as AWS, GCP, or Azure.
- Hands-on experience building APIs and services for data access, metadata management, and platform observability.
- Familiarity with GDPR, SOC 2, HIPAA, and enterprise-grade security practices.
- Effective communication and collaboration skills, with the ability to influence engineering and non-engineering audiences.
- Experience in a startup or high-growth SaaS environment.

## Nice-to-Haves
- Exposure to AI/ML data pipelines or real-time analytics platforms.
- Production experience with Apache Iceberg, Structured Streaming, Kafka on MSK, AWS S3, AWS Glue, MWAA, Trino, or Athena.
- Expertise in Spark performance tuning, including shuffle behavior, partition strategies, memory pressure, Catalyst optimization, and Spark UI analysis.
- Experience choosing between PySpark and Scala Spark for production workloads.

## Compensation and Benefits
- The posting does not specify compensation or benefits.

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