The Sr Data Analyst is an experienced analytics professional who turns complex, cross‑functional data into clear, actionable insights that drive business outcomes as a consultative partner. This role advocates for analytical rigor, designs advanced BI assets, mentors junior analysts, and partners with business, engineering, and governance to improve decision quality and operational performance. Work emphasizes analytics using Databricks, SQL, R, Power BI, Python, and the Azure data stack.
At this time, we are NOT considering applicants that require immigration sponsorship (additional work authorization or permanent work authorization) now or in the future to work in the United States. This includes, but IS NOT LIMITED TO: F1-OPT, F1-CPT, H-1B, TN, L-1, J-1, etc.
Benefits
Our employees enjoy a generous package of benefits that we are thrilled to provide, and feel is part of what makes us different as an employer. We value our team members, and this is one way we can show it.
Benefits include:
-PTO, holiday pay and holiday of choice
-401(k) match
-Life insurance
-Short-term disability
-Health, dental and vision insurance
-Maternity/paternity leave
-Health savings account (HSA)
-Flex spending accounts (FSA) – health and dependent
Position Responsibilities may include, but not limited to
- Support high‑impact analytics initiatives from problem framing through delivery; quantify value, design robust analyses, and communicate recommendations to business partners and executives
- Partner with business leaders to identify analytics opportunities and deliver actionable insights. Present findings and recommendations to partners and leadership in clear, compelling formats
- Develop analytics products and solutions using Databricks, modern Business and Artificial Intelligence tools and Agile principles
- Implement advanced analytics where applicable, leveraging Python for advanced analytics, automation, and integration with Databricks workflows
- Architect and publish trusted Power BI datasets and dashboards (DAX, Power Query, semantic models), following standards for usability and adoption
- Build performant Databricks workflows (notebooks, jobs, SQL Warehouses) to wrangle large datasets, engineer features, and automate recurring analyses
- Develop Python scripts for automation, data wrangling, and integration with Databricks and Azure services
- Partner with Data Engineering for scalable data solutions
- Own analysis quality: data validation, experiment/study design, sensitivity checks, and reproducibility (versioning, documentation)
- Define and monitor KPIs; create and make improvement recommendations based on scorecards and operational reporting that tie directly to business objectives
- Demonstrate advanced and compelling data storytelling, statistical thinking, and visualization craftsmanship
- Collaborate with Data Governance and Compliance to ensure appropriate use of PHI and adherence to privacy/security controls
- Facilitate data stewardship and literacy across the business
- Drive adoption of data products to scale data value
- Stay current with emerging analytics methodologies, technologies and capabilities and apply for continuous improvement
Required Skills and Experience
- Bachelor’s degree in Data Science, Computer Science, Statistics, Economics or related field
- 4-8+ years’ experience in analytics roles, including 3+ years leading projects
- Proven impact delivering analytics in complex environments (multi‑source data, ambiguous scope) with measurable business outcomes
- Experience operating in healthcare data environments (or demonstrated ability to quickly adapt to such contexts)
- Statistical and financial analytics expertise with deep understanding of appropriate study design and analysis techniques and business case development
- Azure Data Stack: Data Factory, ADLS, Synapse/Fabric pipelines; familiarity with security and governance features
- Databricks: Spark/SQL, notebooks & jobs, performance tuning, SQL Warehouses
- SQL: Strong proficiency (ANSI/T‑SQL); query optimization over large, partitioned tables
- R: Applied analytics using tidyverse/ggplot2; reproducible workflows; statistical testing and modeling fundamentals
- Python: Data wrangling, automation, integration with Databricks and Azure services
- Fabric and Power BI: Data modeling, DAX, Power Query (M), calculation groups, row‑level security, deployment pipelines
- Versioning & Reproducibility: Git‑based workflows; disciplined documentation and peer review
- Executive storytelling: distill and translate complex analyses into clear narratives and recommended actions or analytics solutions
- Stakeholder partnership: influence cross‑functional partners; set expectations and drive alignment
- Demonstrated ability to deliver projects with undefined, large and/or complex scope
- Agile delivery
- Data storytelling: leverage strong visualization and communication skills to translate data into action
- Product mindset: understand and define problem statements, success metrics, and iterate with feedback – drives adoption of analytics products and solutions
- Ownership & judgment: operate independently, make sound trade‑offs, and uphold high quality standards
Preferred Skills and Experience
- Master’s degree in Economics, Statistics, Data Science, Computer Science or related field
- Certifications in Databricks, Power BI, or cloud platforms (Azure preferred)
- Experience with machine learning frameworks and MLOps practices
- Familiarity with data governance tools and compliance standards
- Knowledge of advanced BI features (Power BI Copilot, AI-driven analytics)
- Familiarity with healthcare data, groupers and policies
- Product management training or analytics product delivery experience
Physical Requirements
- Repetitive motions that include the wrists, hands and/or fingers
- Sedentary work that primarily involves sitting, remaining in a stationary position for prolonged periods
- Visual perception to perform job including peripheral vision, depth perception, and the ability to adjust focus
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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