How you’ll demonstrate Ownership

Cogniters we are looking for: We are looking for a Sr. Manager, Analytics & Operations Engineering based at Global HQ in Tempe, AZ who treats data and analytics as the operating system for a world‑class professional services organization—not an IT project. You are an entrepreneurial technical leader who builds data platforms from the ground up, turning enterprise data into decision‑ready intelligence for capacity planning, financial forecasting, and strategic execution across a global Value Delivery organization. 

You are deeply technical in Python and cloud engineering, fluent in services operations (utilization, margin, capacity, revenue recognition), and comfortable independently identifying high‑impact problems, designing analytical solutions, and shipping production‑grade tools without a product manager or engineering team. You can debug a Salesforce API integration late in the day and present scenario‑based capacity models to the Chief Services Officer the next morning, always treating data as leverage to multiply the impact of delivery leaders across regions.

 

Data platform engineering and infrastructure

• Own the Value Delivery analytics platform: internal dashboards, automated reports, and data pipelines serving leaders across regions, Finance, and executive teams.​
• Build and maintain automated data pipelines from Salesforce, NetSuite, and finance data warehouses using Python (Pandas, NumPy) and SQL to deliver clean, reliable datasets.​
• Own Azure cloud infrastructure (web app hosting, serverless functions, object storage, managed databases, CI/CD via GitHub Actions, authentication) with end‑to‑end responsibility for reliability, security, and data quality.​
• Integrate with enterprise systems through robust REST, SOQL, and SuiteQL APIs, aligning on data models and definitions with Sales Ops, Finance, and IT.​
• Design and build interactive dashboards using Streamlit or similar frameworks that provide real‑time visibility into capacity, utilization, project financials, pipeline, and delivery risk.​

Services capacity, revenue, and margin forecasting

• Own global capacity forecasting, modeling demand (pipeline, backlog, strategic bets) against resource supply by role, level, and region, and translate outputs into hiring plans, contractor usage, and delivery commitments.​
• Support budgeting and reforecasting by performing top‑down and bottom‑up revenue and margin analysis for the Value Delivery P&L, validating Finance projections against operational data.​
• Build financial models that quantify the impact of pricing changes, delivery model shifts, partner mix, and bench strategy, highlighting margin risks and opportunities across the portfolio.​

KPI engineering and measurement infrastructure

• Define and operationalize core KPIs for Value Delivery operations (utilization, project margins, capacity vs demand, forecast accuracy, time‑to‑value, timecard compliance, partner contribution) and maintain a global dashboard for executives.​
• Where data is missing, create the tools and processes to capture it and move the organization from anecdote to metric‑driven decision‑making.​

Strategic analysis, automation, and cross‑functional partnership

• Conduct targeted analyses and scenario modeling on topics such as partner vs FTE trade‑offs, offering profitability, regional efficiency, and pricing optimization, turning findings into concise executive‑ready recommendations.​
• Proactively identify repetitive workflows across Value Delivery and automate reports, data refreshes, alerts, and self‑service tools that reduce ad‑hoc analysis and operational friction.​
• Serve as the technical partner to the VP, Operations – Value Delivery and Director, Delivery Excellence, ensuring analytics directly inform delivery standards, playbooks, portfolio optimization, and partner performance management.

 

The Impact you bring to Cognite

• Data‑driven operations: You transform Value Delivery from intuition‑based to insight‑driven, enabling faster, better decisions on capacity, hiring, pricing, and portfolio management.
• Executive leverage: You multiply the impact of senior services leadership by providing the analytical foundation and scenarios for multi‑million‑dollar investment and go‑to‑market decisions.
• Operational efficiency: You eliminate large amounts of manual work through automation, freeing leaders to focus on customers and strategy.
• ​Financial performance: Your models and forecasts improve utilization, profitability, and revenue predictability.
• Scalable infrastructure: You build analytics systems that scale with the business—from 100 to hundreds of delivery professionals—without accumulating technical debt or quality issues

Required Qualifications

• 7+ years in analytics, data engineering, or technical operations within high‑growth SaaS, enterprise software, professional services, or management consulting.
• ​Exceptional Python skills (Pandas, NumPy, ETL, automation) and strong SQL for complex querying and aggregation.
• ​Hands‑on experience with Azure (strongly preferred) or AWS/GCP: web app hosting, serverless functions, object storage, managed databases, and CI/CD (i.e. GitHub Actions).
• Proven ability to build production‑grade data pipelines and API integrations (REST, Salesforce/SOQL, NetSuite) with reliability, monitoring, and error handling.
• Professional services or operations analytics domain knowledge (capacity planning, utilization tracking, margin and project economics, resource management).
• ​Demonstrated success as the sole technical owner of an internal platform, independently translating business problems into technical solutions and tools.

 

A snapshot of our many perks and benefits as a Cogniter