• Regularly design, develop, and maintain data pipelines and ML workflows to support operational and analytical needs • Write clean, efficient, and well-documented Python code for data processing, model development, and automation tasks • Analyze and interpret complex datasets, including time-series and machine health data to surface meaningful insights and support decision-making • Build, validate, and monitor AI/ML models in production, proactively identifying and resolving performance issues • Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders across teams • Participate in cross-functional meetings and planning sessions to align data engineering efforts with broader business goals • Stay current with advancements in AI/ML techniques, tools, and industry-specific applications, particularly within power, oil, and gas environments • Document processes, models, and systems in a way that supports knowledge sharing and team continuity

• Manage day-to-day IT operational services, ensuring stability, availability, and performance of critical systems and infrastructure. • Monitor operational KPIs, SLAs, OLAs, and service quality metrics. • Coordinate incident, problem, change, and service request management processes. • Lead operational governance meetings and service review sessions. • Ensure operational compliance with internal standards and IT governance frameworks. • Lead process mapping initiatives for IT operations and service management workflows. • Analyze current-state processes and design optimized future-state operational models. • Identify process gaps, inefficiencies, bottlenecks, and operational risks. • Document end-to-end workflows, SOPs, RACI matrices, and operational procedures. • Standardize operational routines and governance practices across teams. • Identify recurring operational issues and implement corrective and preventive actions. • Coordinate root cause analysis (RCA) and continuous service improvement plans. • Support transition from project delivery into stable operational support models. • Ensure operational readiness for new services, applications, and infrastructure deployments. • Identify automation opportunities across operational and service management processes. • Partner with infrastructure, cloud, DevOps, and engineering teams to implement automation solutions. • Improve operational efficiency through workflow automation, monitoring enhancements, and self-service capabilities. • Promote a culture of continuous improvement and operational excellence. • Support implementation and optimization of ITSM and monitoring tools. • Establish and maintain strong operational routines with key business and IT stakeholders. • Act as the primary point of contact for operational service discussions and escalations. • Facilitate recurring governance meetings, status reviews, and executive reporting. • Ensure clear communication of operational performance, risks, and improvement initiatives. • Build collaborative relationships across technical and business teams.

• Architect and design machine learning systems capable of processing millions of real-time data points, leveraging feature stores, real-time inference pipelines, and scalable model serving frameworks to ensure high performance and low latency • Drive architectural decision-making for data and ML systems through RFC processes, ensuring solutions are scalable, statistically sound, and future-proof • Contribute hands-on to data and ML challenges, including building data architectures and high-performance feature engineering pipelines • Collaborate closely with DevOps teams to ensure ML infrastructure (Kubernetes, cloud platforms, GPU clusters) is optimized for training and inference workloads • Define and evolve scalable data architectures that support advanced analytics, predictive modeling, and business growth • Mentor and guide Senior Data Scientists and ML Engineers, fostering strong practices in statistical rigor, MLOps, and systems thinking • Support other tasks or projects as assigned to meet team and business needs

As a Senior Software Engineer, Data, you will be a key contributor driving the design, implementation, and optimization of FloQast’s core data platform. You will build and scale the critical systems that power data ingestion, storage, processing, and access across our product and analytics pipelines. Working closely with cross-functional teams, you will ensure our data infrastructure remains highly reliable, scalable, and secure, enabling engineering and business operations to build on a solid data foundation. What You'll Do - 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. What You'll Bring - 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. #BI-Remote #LI-Hyrbid #LI-JM1 This job posting is for our Senior Software Engineer, Data the base pay range for this position is $144,000 - $216,000. Compensation is not limited to base salary. FloQast values our Total Rewards, and offers a competitive and elaborate Benefits Package including, but not limited to, Medical, Dental, Vision, Family Forming benefits, Life & Disability Insurance, and Unlimited Vacation. FloQast reserves the right to amend, change, alter, and revise pay ranges and benefits offerings at any time. All applicants acknowledge that by applying to this position you understand that this specific pay range is contingent upon meeting the qualifications and requirements of the role, and for the successful completion of the interview selection and process. It is at the Company's discretion to determine what pay is provided to a candidate within the range associated with the role. About FloQast: FloQast is the leading AI-powered Accounting Transformation Platform, uniquely built by former accountants for accountants. We automate complex, recurring accounting workflows—transforming preparers into strategic reviewers and relieving accountants from tedious manual work. Our cloud-based solution is trusted by over 3,500 world-class accounting teams, including Lululemon, Doordash, and the MLB, to drive collaboration and financial accuracy. Driven by a mission to continuously elevate the profession, FloQast is redefining both the practice and the perception of accounting on a global scale. Our values act as a guiding compass, shaping every decision we make, and are non-negotiable, particularly in our hiring process. Alongside our employees, partners, and customers, we embody these values every day: Unwaveringly Authentic Ambitious with Integrity Empowered to Grow Committed to Collaboration Customer Obsessed in All Ways 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! FloQast is regularly rated as a Best Place to Work! - Inc. Magazine’s Best Workplaces in 2025, 2024, 2023, 2022, and 2021 - Best Places to Work by LA Business Journal since 2017 (that’s 9 years!) - Built In’s ​​Best Place to Work in Los Angeles 7 years in a row! Because we are Customer Obsessed in All Ways, check out what our customers have to say about FloQast on G2 Crowd. If this aligns closely with what you are looking for, hit “Apply” and come join our growing team! FloQast, Inc is committed to operating fair and unbiased recruitment procedures allowing all applicants an equal opportunity for employment, free from discrimination on the basis of religion, race, sex, age, sexual orientation, disability, color, ethnic or national origin, or any other classification as may be protected by applicable law. We aim to recruit the right people for the jobs we have to offer, and to assess applications on the basis of relevant skills, education, and experience. We welcome people of different backgrounds, experiences, abilities, and perspectives. We are an equal opportunity employer and strive to provide a professional and welcoming workplace for all employees. Link to FloQast Recruiting AI Usage Policy