Floqast11mo ago

Senior Staff Engineer, Data

United States·San JoseFull-timesenior

OtherData EngineeringStaff Engineer

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Quick Summary

Overview

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.

Technical Tools

airflowawsazuredbtgcpkafkasnowflakedistributed-systemsetlsaasstreaming-data

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. Your work will enable teams across engineering, product, and business operations to build on a reliable, scalable, and secure data foundation.

Visa sponsorship is NOT available at this time

Data Platform Architecture: Lead the design of scalable and reliable data pipelines, storage solutions, and access layers using modern cloud-native technologies.

Foundational Systems: Own and evolve the core data platform components (e.g., event streaming, lakehouse architecture, batch & streaming ETL, data cataloging).

Data Governance: Define best practices for data quality, lineage, privacy, and access control to ensure regulatory compliance and trust in the data.

Cross-functional Collaboration: Work closely with Product, Analytics, Infrastructure, and Security teams to align data platform capabilities with organizational goals.

Technical Leadership: Mentor engineers across the organization, establish coding and architectural standards, and influence the strategic direction of the platform.

Innovation & Modernization: Evaluate and integrate emerging technologies that improve performance, observability, developer experience, and cost efficiency.

10+ years of software engineering experience with deep expertise in data infrastructure, distributed systems, or backend platform engineering.

Proven track record of designing and delivering production-grade data platforms at scale (e.g., supporting hundreds of TBs of data, thousands of jobs/day).

Strong experience with tools like Snowflake, dbt, Kafka, Airflow, Spark, and cloud-native technologies (e.g., AWS, GCP, or Azure).

Hands-on experience building APIs and services for data access, metadata management, and platform observability.

Familiarity with data privacy regulations (GDPR, SOC2, HIPAA) and enterprise-grade security practices.

Effective communicator and collaborator who can influence engineering and non-engineering audiences alike.

Experience in a startup or high-growth SaaS environment.

Exposure to AI/ML data pipelines or real-time analytics platforms.