Senior Software Engineer, Data

FloQast is the leading AI-powered Accounting Transformation Platform, uniquely built by former accountants for accountants. As a Senior Software Engineer, Data, you will drive the design, implementation, and optimization of FloQast’s core data platform, ensuring the infrastructure is reliable, scalable, and secure while collaborating with cross-functional teams.

Responsibilities:

• Data Platform Development: Contribute to the design and implementation of scalable, reliable data pipelines, storage solutions, and efficient access layers using modern cloud-native technologies
• Pipeline Execution: Build, optimize, and maintain core data platform components, including event streaming infrastructure, lakehouse storage layers, and both batch and streaming ETL workflows
• Data Quality & Security: Implement best practices for data quality, data lineage, and access controls to ensure robust security, regulatory compliance, and overall trust in our data assets
• Cross-functional Collaboration: Work closely with Product, Analytics, Infrastructure, and Security teams to deliver data capabilities that support team-specific and organizational goals
• Team Mentorship: Provide technical guidance and code reviews for other engineers on the team, helping to champion clean code, consistent engineering standards, and platform stability
• Performance & Observability: Evaluate, test, and integrate new tools and technologies that actively improve data pipeline performance, systems observability, and overall cost efficiency

Requirements:

• 7+ years of software engineering experience with a strong background in data infrastructure, distributed systems, or backend data platform engineering
• Proven experience building and maintaining production-grade data pipelines at scale (e.g., handling large data volumes, optimizing job execution, and ensuring data reliability)
• Strong hands-on experience with modern data ecosystem tools, such as Snowflake, dbt, Kafka, Airflow, Spark, and cloud-native services (e.g., AWS, GCP, or Azure)
• Experience building and integrating APIs and services for data ingestion, access, and pipeline observability
• Good understanding of secure data handling, including familiarity with enterprise-grade security practices and data privacy considerations (such as SOC2 or GDPR)
• Strong communication and collaboration skills, with a track record of partnering successfully across engineering and analytics teams
• Experience working within a startup or high-growth SaaS environment is highly preferred
• Exposure to or interest in AI/ML data pipelines or real-time analytics architectures