Product Manager

📋 Description

• • As a Product Manager at Flexera, you will be at the forefront of a transformative initiative, tasked with building and scaling our cutting-edge Data & AI Infrastructure FinOps platform from the ground up. This pivotal role demands a strategic thinker with a proven ability to execute, defining and delivering next-generation experiences for cost visibility, workload optimization, and autonomous performance tuning specifically within the Snowflake and Databricks ecosystems.
• • You will own the product strategy for an immense, untapped market opportunity estimated at $100 billion, situated at the critical intersection of Cloud Cost Optimization, FinOps, and AI-driven data infrastructure performance management. Your vision will shape how enterprises manage and optimize their most critical data assets.
• • Your primary focus will be the development and launch of a comprehensive FinOps experience tailored for Snowflake and Databricks. This includes defining granular cost attribution models that track expenses at the warehouse, cluster, workload, team, and even query levels. You will establish robust unit economics frameworks, enabling the calculation of cost per dashboard, cost per ML job, and cost per pipeline, providing unprecedented financial clarity.
• • Furthermore, you will be instrumental in building essential FinOps workflows, encompassing budgeting, forecasting, anomaly detection, and governance. A key aspect of your role will be creating persona-based experiences, ensuring that the platform delivers tailored value to Data Engineers, BI professionals, ML engineers, Finance teams, and Platform administrators.
• • You will also drive the creation of best-in-class performance optimization features. This involves developing tools for cluster/warehouse efficiency scoring and identifying idle or over-provisioned resources. You will architect recommendation engines that suggest auto-sizing for warehouses and clusters, provide guidance on caching and materialization strategies, and offer insights into storage and compute tuning.
• • A significant part of your responsibility will be to establish measurable performance benchmarks, ensuring our solutions not only meet but exceed competitor offerings in efficiency and speed.
• • Delving deeper into workload intelligence, you will create sophisticated visibility and tuning capabilities for both SQL and Spark workloads. This encompasses ETL pipelines, streaming data, and ML training jobs, providing developers with actionable, user-friendly tuning guidance to enhance performance and reduce costs.
• • A truly innovative aspect of this role involves defining and shipping AI-driven autonomous optimization agents. These agents will continuously monitor infrastructure, proactively tune for cost and performance, and execute automated remediation actions. You will design sophisticated closed-loop optimization systems, incorporating essential guardrails, explainability layers, and trust frameworks to ensure the safe and effective operation of autonomous actions.
• • You will also introduce simulation environments, allowing users to preview the cost and latency impact of proposed changes before they are implemented, thereby mitigating risks and fostering confidence in optimization strategies.
• • Your key responsibilities will extend to owning the product vision, strategy, and roadmap execution. You will collaborate closely with Engineering and Go-To-Market (GTM) teams to deliver category-defining capabilities that resonate with the market.
• • You will define and track clear success metrics, including Cost Savings Percentage, Performance Gains Percentage, user adoption rates, and the effectiveness of autonomous actions. Competitive benchmarking and the development of differentiation strategies will be crucial for market success.
• • A critical skill will be your ability to translate deep technical complexity into clear, compelling customer value narratives that resonate with both technical and business stakeholders.
• • You will actively engage in customer discovery, interacting with Data Engineers, FinOps leaders, Platform teams, and CIOs to gather insights and validate product direction.
• • This role is vital because Data & AI infrastructure is rapidly becoming the largest expenditure in enterprise cloud spend. Current FinOps tooling for data warehouses, lakehouses, and AI workloads is often immature. You will be defining the next generation of optimization, acting as the intelligent layer between cloud providers and enterprise data teams, transforming reactive cost reporting into proactive, autonomous infrastructure intelligence.