Associate Director Finops Practitioner Data Cloud Platforms

Fin Ops Practitioner – Data Cloud Fin Ops

Are you ready to make an impact at DTCC?

Do you want to work on innovative projects, collaborate with a dynamic and supportive team, and receive investment in your professional development? At DTCC, we are at the forefront of innovation in the financial markets. We are committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact. We foster a thriving internal community and are committed to creating a workplace that looks like the world that we serve.

The Fin Ops Practitioner – Data Cloud Fin Ops is responsible for optimizing, governing, and managing the financial performance of cloud-based data platforms and services. This role combines cloud financial management, data engineering knowledge, financial analysis, and operational governance to ensure that data infrastructure delivers maximum business value at an optimized cost.

The practitioner partners with Finance, Cloud Engineering, Data Engineering, Enterprise Architecture, Procurement, and business stakeholders to establish cost transparency, allocate spending to business units and data products, optimize consumption, and embed Fin Ops principles into the data platform lifecycle.

The role focuses on cloud data services such as data warehouses, data lakes, lake houses, data integration pipelines, streaming platforms, analytics environments, and AI/ML workloads across data cloud platforms such as Snowflake, AWS, Microsoft Azure, Google Cloud, Databricks, and other cloud data ecosystems.

Your Primary Responsibilities:

• Monitor and analyze cloud data platform spending across services, environments, business units, projects, and data products.
• Develop dashboards and reports to track data cloud expenditure, consumption trends, unit costs, and budget utilization.
• Build cost allocation and chargeback/showback models for data platforms and shared data services.
• Identify cost anomalies, unexpected consumption spikes, and spending trends, and coordinate corrective actions.
• Reconcile cloud provider invoices and platform usage reports with internal financial records.
• Analyze consumption patterns across data warehouses, lake houses, ETL/ELT pipelines, streaming workloads, and analytical queries.
• Identify optimization opportunities related to compute sizing, cluster utilization, workload scheduling, autoscaling, and resource concurrency.
• Optimize query performance and workload design in collaboration with data engineering teams to reduce processing costs.
• Evaluate workload placement and platform choices based on performance, reliability, scalability, and total cost of ownership.
• Assess the financial impact of architectural decisions, including real-time versus batch processing and cloud-native versus managed data services.
• Develop and maintain budgets and forecasts for cloud data platforms and associated services.
• Analyze actual spending against budgets, forecasts, business demand, and historical consumption.
• Build predictive cost models based on data growth, workload volumes, user adoption, and business initiatives.
• Support financial planning for new data products, platform migrations, analytics initiatives, and AI workloads.
• Prepare financial variance analysis and communicate cost drivers, risks, and corrective actions to leadership.
• Implement Fin Ops policies, controls, standards, and operating procedures for data cloud services.
• Establish ownership for data platform costs across engineering teams, product owners, and business stakeholders.
• Establish governance for budget thresholds, anomaly alerts, cost optimization actions, and escalation procedures.
• Develop standardized KPIs and maturity assessments to measure the effectiveness of data cloud Fin Ops.
• Define and…