Data and Insight Analyst

Overview

The Data & Insights Analyst is responsible for leading the design, architecture, and delivery of advanced analytics, reporting, and data-driven solutions that generate measurable business value. This role operates as a strategic partner to business and technical stakeholders, translating complex data into actionable insights and scalable solutions. The Analyst plays a key role in shaping data strategy, advancing modern data platforms (including cloud and big data ecosystems), and embedding AI/ML capabilities into analytics workflows.

This individual is expected to influence best practices, and drive innovation across the Analytics function. This role requires a balance of hands‑on technical expertise, business acumen, and leadership within an Agile delivery environment.

• Support the architecture, design, and development of scalable analytics and reporting solutions across enterprise data platforms.
• Partner with business stakeholders to define analytical strategies, frame problems, and deliver insights that drive decision‑making.
• Design and implement end‑to‑end data pipelines and workflows using modern big data and cloud technologies.
• Develop and optimize data models, dashboards, and self‑service reporting solutions using tools such as Tableau, Micro Strategy, or similar platforms.
• Leverage Databricks platform capabilities (Delta Lake, Spark, notebooks, workflows) to build and maintain scalable data and analytics solutions.
• Integrate AI/ML models and advanced analytics into production workflows, including predictive modeling, anomaly detection, and automation of insights.
• Drive automation and operationalization of analytics solutions, including CI/CD practices and data quality monitoring.
• Provide technical leadership in code reviews, design reviews, and architecture decisions, ensuring adherence to best practices.
• Mentor and guide junior analysts and engineers, contributing to team capability development.
• Collaborate with cross‑functional teams to ensure data governance, security, and compliance standards are met.
• Lead or contribute to the Analytics Center of Excellence, promoting reusable frameworks, standards, and innovation.
• Communicate complex analytical findings clearly to stakeholders at all levels, including executive audiences.
• Deliver solutions using Agile methodologies and actively contribute to sprint planning, backlog refinement, and retrospectives.
• Maintain documentation, data lineage, and knowledge repositories for all solutions.
• Complete all responsibilities as outlined in the annual performance review and/or goal setting.
• Complete all special projects and other duties as assigned.
• Must be able to perform duties with or without reasonable accommodation.

Minimum Qualifications:

• Bachelor’s degree in Business Analytics, Finance, Economics, Statistics, Mathematics, Data Science, Information Systems, or related quantitative/business field.
• 4+ years of experience in advanced analytics, data engineering, or data science roles.
• Proven experience delivering actionable insights and business impact from complex datasets.
• Experience working in modern data platforms, including cloud‑based or distributed environments.
• Experience in healthcare analytics, claims data, or payment integrity strongly preferred.

Technical

Skills:

• Advanced proficiency in SQL across multiple platforms (e.g., Oracle, PostgreSQL, MySQL).
• Strong programming skills in Python, Spark (PySpark/Scala), or R.
• Hands‑on experience with Databricks (Delta Lake, Spark optimization, job orchestration, MLflow).
• Experience building and deploying machine learning models and working with AI frameworks (e.g., scikit‑learn, Tensor Flow, or similar).
• Familiarity with Generative AI concepts, including prompt engineering, embeddings, or LLM‑powered analytics use cases.
• Experience with data pipeline orchestration tools and workflow automation.
• Strong experience with business intelligence tools (Tableau, Micro Strategy, Power BI, etc.).
• Knowledge of data warehousing, data modeling, and lakehouse architectures.
• Experience with big data technologies (Hadoop ecosystem, Spark, etc.).

Analytical & Business

Skills:

• Strong foundation in…