Data Analyst, L&C Strategy and Operations: Data Analytics and Technology Focus
Join our LCG Operations & Strategy analytics team to build, enhance and maintain the analytics, dashboards and data foundations teams and leaders use to run the business every day. You’ll turn complex data from our Azure data lake into clear, automated Power BI visualizations and insights that drive decisions, unlock efficiencies, and strengthen governance. In this role, you’ll own end‑to‑end solutions—from designing new tables and SQL logic to managing permissions across Power BI and SharePoint—while applying Python for deeper analytical and forecasting methods.
You’ll also explore and apply emerging Generative and Agentic AI tools to accelerate insight generation, automate repeatable analytics tasks, as well as enhance dashboard and data development and quality assurance workflows. You’ll gain broad exposure to senior stakeholders, modern Azure tooling, and best‑in‑class delivery practices in a supportive, global hybrid work environment.
Position Responsibilities:
Partner with Stakeholders to develop intuitive, user-based solutions that resonate with and are embraced by non-technical users. Leveraging strong communication skills and a growth mindset to ensure solutions address both macro and micro perspectives is critical. Specific elements of these solutions include:
Building, enhancing, and automating advanced Power BI dashboards, optimizing data models/DAX, refresh pipelines, and deployment pipelines; implement and maintain row‑/object‑level security.
Adapting dashboards based on stakeholder’s analytics needs and continuous maintenance of the analytics and technology stream assets.
Performing data preprocessing, transformation, and analysis across multiple sources/datasets to develop comprehensive, insight‑driven dashboards that support effective decision‑making for senior leadership.
Designing and creating new tables and views; write performant SQL to model, transform, and validate data sourced from the Azure data lake (e.g., ADLS Gen2) for analytics use.
Developing reliable automations (e.g., data refresh orchestration, parameterized datasets, alerting) and establish monitoring to ensure dashboard/data SLAs.
Managing permissions and access controls across Power BI workspaces/datasets/reports and SharePoint sites/libraries to meet least‑privilege and audit requirements.
Using Python (pandas, scikit‑learn, notebooks) for advanced analytics such as forecasting, segmentation, anomaly detection, and feature engineering, package findings into reusable assets.
Leveraging Generative AI tools (e.g., Copilot, Azure OpenAI) to accelerate analysis, generate documentation, support exploratory analytics, and streamline development workflows.
Identifying opportunities to embed GenAI-driven automation into data pipelines, reporting processes, and stakeholder deliverables.
Using GenAI-based assistants to enhance SQL, Python, and Power BI development efficiency while maintaining governance and quality standards.
Developing and leading requirements gathering, workshops and training sessions for the development and implementation of relevant solutions that incorporate change enablement and user design principles
Required Qualifications:
4 - 5 years of professional experience in data analytics or business intelligence.
4+ years building advanced Power BI solutions (data modeling, complex DAX, Power Query, RLS/OLS, deployment pipelines).
4+ years writing SQL (joins, window functions, performance tuning) and 3+ years working in an Azure data lake environment.
Demonstrated experience creating new tables/views and preparing curated datasets for reporting and analysis.
Proven track record automating dashboards (e.g., scheduled refreshes, pipeline‑based deployments, alerts) and managing permissions at workspace/dataset/report levels.
Experience administering SharePoint sites and managing permissions (site/library access, groups, links, sensitivity).
Proficiency with Python for analytics (data wrangling, modeling, visualization) and documenting code/notebooks.
Bachelor’s degree in data/computer science, Engineering, Analytics, or a related field.
Familiarity with Generative AI tools and workflows (e.g., Microsoft Copilot, Azure…
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