Data Analyst

• Analyze Snowflake, cloud, and data platform billing data to identify spend drivers, usage trends, and cost optimization opportunities
• Build, maintain, and interpret dashboards, KPIs, and reporting that enable cost transparency, showback, and future chargeback
• Partner with engineering and product teams to explain cost variance, validate optimization recommendations, and support architectural trade-off decisions
• Support financial planning activities, including forecasting, budgeting, and variance analysis, in close alignment with Finance
• Contribute to cloud and platform cost governance by monitoring utilization, identifying risks, and tracking savings initiatives
• Produce clear, credible insights and narratives that enable informed cost decisions across technical and financial audiences
• Support ongoing improvement of FinOps processes, tooling, and data quality
• Participate in recurring reviews of spend, trends, and investment priorities with cross-functional stakeholders

FinOps Data Analyst – Cost Insight, Business Alignment

• Play a meaningful role in delivering high-quality, impactful analytics and insights to Talent, HR and business leaders.
• Lead efforts to transform candidate, associate, and operational data into actionable insights that inform strategic decision-making across Talent Acquisition, Talent Management, and Talent Learning and Development.
• Design and implement data workflows, models, and dashboards that make talent data accessible, interpretable, and impactful.
• Support workforce data initiatives, ensuring analytics solutions are aligned with business needs and delivered efficiently.
• Uncover trends, tell compelling data stories, and translate complex analytics into business recommendations.
• Develop and maintain robust data pipelines using SQL (Snowflake, SQL Server), with a focus on performance tuning and query optimization.
• Create and enhance interactive dashboards and visualizations in Tableau and Power BI to support leadership with real-time insights and compelling data storytelling.
• Collaborate cross-functionally with Talent and Business leaders to gather requirements, translate business needs into analytics solutions, and deliver insights that influence strategic decisions.
• Communicate and socialize analytical findings by translating complex data into clear, actionable business recommendations through presentations and storytelling.
• Provide mentorship and thought leadership to team members and cross-functional partners, fostering a culture of analytical excellence and continuous learning.

Senior Manager, Data Analytics, Insights

• Maintain the KPI standards for Customer Support: document how each metric is calculated and interpreted, keep definitions current across data platforms, and flag to leadership when targets may need adjustment.
• Build and maintain dashboards in Omni Analytics (our BI platform) that serve analyst, manager, and leadership audiences; maintain the semantic layer and metric definitions so every team measures the same things the same way.
• Produce formal analyses and recommendations on volume trends, resolution efficiency, CSAT, contact rate, and cost performance; frame findings in terms of business impact, not just numbers.
• Identify anomalies and performance gaps in Support data; bring a recommended course of action to leadership rather than a flag, and track the response through to resolution.
• Consult on SQL, Snowflake, and BI standards used for Support reporting; ensure Support modeling approach, query patterns, and tooling match organizational standards.
• Lead metric alignment conversations with Data, Product, and Engineering; represent Support's analytical interests and keep shared definitions from drifting.
• Triage and scope ad hoc analysis requests from across the organization; exercise judgment on urgency, feasibility, and which questions are worth answering.

• Serve as Manager for analytics and insights work reporting on various improvement initiatives.
• Drive leading class analytics and insight generation.
• Build cross-functional relationships with business and analytics colleagues.
• Provide insights enabling data-driven decisions for strategic objectives.

Manager, Data Analytics, Insights

• Engage with partners across business, analytics, and technical teams to enable easier access to improved data analytics
• Provide greater insights and decision-making capabilities to support strategic initiatives
• Work closely with a highly skilled, multidisciplinary team, fostering strong collaboration across Fidelity Technology
• Ensure timely delivery and successful outcomes
• Part of our Portfolio and Program team in Enterprise Data and AI that oversees data and AI portfolios and execution of large, complex cross BU strategic initiatives
• Contribute daily to making a difference in Fidelity’s technology advancement

Senior Data Analyst

• Partner across the organization in developing tools and supporting data infrastructure to meet reporting and analytics capability demands
• Deliver insights into business performance and develop predictive analytics that inform strategic decision-making
• Collaborate with business leaders, technology partners, and data teams to advance analytics strategy
• Contribute to data governance routines and ensure availability of trusted, timely data to enhance consistency, execution, and decision quality across the enterprise

• Lead the Business and Data Analytics team
• Deliver actionable insights and dashboards
• Partner closely with FW leaders and stakeholders
• Oversight of analytical solutions to improve business performance

Director, Data Analytics, Insights

• Sit with internal stakeholders (Medicare sales, finance, operations, HR) to walk them through Omni dashboards, capture feedback, document defects and change requests, and track them to resolution.
• Make report-side changes in Omni: tile edits, formatting, labels, filters, and layout. Escalate anything that touches dbt models or schema to the Interim Head of Analytics.
• Write SQL to spot-check numbers, audit data quality, and answer one-off questions from the business.
• Maintain and update the entity-relationship documentation for the Mart layer as the schema evolves.
• Reconcile reported numbers against source systems (Sabal, Atlantis, Paylocity, Sonar, Retreaver) when discrepancies are flagged.
• Own a clean, organized backlog of business requests and known issues so nothing falls through the cracks.

Junior Data Analyst

• Manage within the WI Internal Analytics, Insights and Reporting team.
• Partner to build cross-functional relationships with business and analytics colleagues.
• Drive improvement and efficiencies for Fidelity Workplace Investing (WI) across diverse solutions and approaches.
• Serve as Manager for analytics and insights work reporting on various improvement initiatives.
• Play a key role in transformation to a platform enabled and capability-led Digital Future.
• Enable Workplace Investments to make data-driven decisions required to meet strategic objectives.

Manager, Data Analytics and Insights

• leverage analytical expertise to deliver data-driven solutions that enhance the effectiveness of Enterprise Talent programs
• Perform exploratory and forensic data analysis to uncover trends, patterns, and anomalies while developing subject-matter expertise across our various Talent data sets
• Synthesize data findings and be able to communicate findings through clear storytelling and presentations that influence decision-making
• Create and enhance interactive dashboards and visualizations in Tableau and Power BI to provide real-time insights
• Develop and optimize Alteryx workflows to deliver scalable talent analytics and workforce insights and automate processes
• Build and maintain data pipelines using SQL (Snowflake, SQL Server);
• Build strong relationships with team members and key business partners to establish trust and maintain solid working relationships
• Collaborate cross-functionally with Talent and Business leaders to gather requirements, translate business needs into analytics solutions, and deliver insights that influence strategic decisions
• Support data governance practices, including documentation and implementation of best practice data standards including process flows, data quality and data definitions
• Proactively seek opportunities to provide valuable insights and receive continuous improvement feedback from our business partners

• Develop and deploy advanced analytical models to improve our understanding of Network supply and demand, identify operational inefficiencies, and deliver actionable recommendations to leadership
• Implement real-time dashboards and reporting to track and assess Network performance against established metrics
• Challenge the status quo and propose and test new strategies for increasing competition and engagement within our service provider network
• Analyze feedback, ratings, and reviews from multiple sources and stakeholders to gain insights into service quality and customer satisfaction
• Develop operational and performance data to generate actionable insights and recommendations for 3rd party service providers
• Analyze the capacity of our Network, identifying gaps and opportunities to improve operational efficiency and service quality
• Lead test and pilots for process changes as a result of analysis and communicate the results to management
• Serve as an internal data analytics expert by ensuring consistency in data analysis methodologies and sharing of best practices.

Lead Data Analyst – Network

• Collect, clean, and analyze financial and operational data from multiple internal systems; use AI-assisted tools (including Claude) to accelerate data validation, anomaly detection, and cross-source reconciliation
• Develop and maintain advanced financial and operational models in Excel — as a designer, not just a user — and leverage Power BI for visualization and Power Query for automated data transformation
• Build and maintain Power Automate workflows to reduce manual reporting steps, automate data refreshes, and improve operational efficiency across finance functions
• Actively use Claude and other AI tools to generate analytical narratives, draft variance explanations, and identify trends that inform strategic recommendations
• Champion AI adoption within the organization by training colleagues, sharing practical use cases, and developing repeatable AI-assisted workflows that teams can adopt
• Serve as an active participant in NELC’s AI governance framework — contributing to the development of responsible use standards, data policies, and compliance guidelines for AI tools in a healthcare environment
• Contribute to the annual budgeting and quarterly forecasting processes, ensuring alignment with organizational goals and leveraging AI tools to improve accuracy and speed
• Analyze monthly financial results and trends to deliver actionable insights and strategic recommendations to senior management
• Identify trends, variances, and anomalies and communicate findings proactively to stakeholders, using AI-generated summaries and dashboards where applicable
• Structure and analyze large, complex data sets to uncover patterns, trends, and business opportunities
• Perform routine data quality checks and reconciliations to ensure consistency across data, reporting, and outcomes
• Collaborate with internal and external stakeholders to gather requirements, validate data, and ensure accuracy in reporting
• Create clear and compelling presentations and reports based on analytical findings and recommendations
• Design, maintain, and enhance dashboards and visualizations that communicate key metrics across the organization
• Maintain knowledge of applicable regulations and policies, including healthcare finance, reimbursement models, and HIPAA requirements as they relate to data and AI use

Financial Data Analyst

• Conduct accurate and timely business analysis and reporting to support and drive business decisions.
• Collaborate with key stakeholders to define key financial and operational metrics.
• Build and maintain models used to project business results; enhance the model where there is business value.
• Ensure analysis and reporting accuracy and integrity; explain performance drivers and provide insights into performance trends.
• Analyze and address data quality issues; test and analyze the impact of system changes to data/reporting infrastructure.
• Develop, test, and deploy automated reporting solutions and automated decision analytics.

Senior Product Data Analyst

• Responsible for the coordination of projects focused on data use and reporting.
• Sets deadlines, assigns responsibilities, and monitors and summarizes progress of projects.
• Identifies and coordinates improvement opportunities, enhancements, and redesign to accomplish greater efficiency.
• Increase operational efficiency by leveraging new technologies through automation.
• Develop and maintain working relationships to enhance ability to meet goals and users’ objectives.
• Recommend appropriate maintenance strategies to ensure uninterrupted systems usage.
• Harmonize codes across datasets where possible to improve designs in report collection.
• Build and monitor data quality rules for use in data warehouses and other data assets to increase amount of data usable for reporting.
• Apply database system rules in order to import non-conformed data for new use.
• Assist business owners with a root cause analysis process for issues discovered during data quality assessment.
• Develop web application presentation and security for web-based data entry and self-service reporting.
• Participate in on-call rotation, as required, for ITS support of computing users.

Data Analyst III – IT Reporting

• Support customer segmentation and book-of-business management for sales and CS teams
• Partner with strategic partners and sales teams to align customer data, track sales/CS performance, and optimize partner engagement
• Manage and maintain CRM data integrity, assisting with development and optimization as needed
• Generate reports for QBRs, including sales funnels, Clarus portal KPIs, forecasting, and performance analytics
• Track and analyze rep activity, sales pipeline metrics, and partner team performance
• Provide insights on CRM utilization and automation opportunities for improved efficiency
• Collaborate with leadership to identify gaps in sales enablement and customer success processes
• Support strategic decision-making through data analysis and performance tracking

Sales Data Analyst

• Partner with key talent stakeholders to intake, catalog, prioritize and execute requests and enhancements to new and existing metrics, reports, discovery boards, dashboards and other tools/resources.
• Develop a deep understanding of the Talent and Culture initiatives and priorities to connect the dots across deliverables and provide deep analytics and insights.
• Proactively manage and deliver projects against key deliverables with a strong rhythm of communication and updates to stakeholders.
• Dive deep into complex enterprise-wide business problems and provide insights into the employee experience.
• Collaborate with team members and business partners to deliver high quality solutions and recommendations to a variety of problems across the employee experience domain.
• Bring data to life through storytelling in a clear and meaningful way to audiences with mixed levels of technical expertise and strong ability to merge context and data for effective messaging and relevance of products.
• Reconcile divergent demands from multiple stakeholders in a fast-paced work environment while prioritizing the support of our Talent function.
• Provide definition, KPI, analysis and interpretation support to HR Leadership for Executive presentations and strategic initiatives.
• Use complex datasets to create and implement new data definitions, KPIs and Metrics in the interest of identifying metrics that matter to the employee's journey.
• Proactively assess the effectiveness of existing tool stack, monitor data accuracy, and consult partners to drive adoption.
• Provide expertise in Workday Reporting & Prism, Looker, and the Google Cloud Platform to ensure People Analytics datasets are accurate, efficient, and meaningful.

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