Analytics Developer III

Role Overview -The Digital & Marketing Analytics team provides advanced analytics products/dashboards and reporting services to stakeholders in the Digital and Marketing teams.



Salary: $115K

Write Up - Required Professional Experience, Technologies & Additional Context

• Summarize exp. they have with enterprise analytical & BI tools (such as, Cognos, Tableau, Qlickview, Excel PowerPivot, SSRS)
• Summarize exp they have with programming languages (such as SAS, SQL, R, or STATA)
• What regulated industry do they have experience in, as an Analytics Developer? (Healthcare, etc)

Baylor Scott & White - Remote. Excluding Baylor Restricted States: California, Hawaii, New Jersey, New York, North Dakota, Oregon, Puerto Rico, Rhode Island, US Virgin Islands, Washington, Wyoming

Analytics Developer III

Direct Hire
*Candidates must complete a background check & drug screen upon offer*



Job Description:
The Digital Analytics team delivers trusted measurement, advanced analytics products, dashboards, reporting, and actionable insights to leaders and stakeholders across the organization.


As a member of the Customer Analytics team, the Analytics Developer III serves as a high-impact, leadership-facing analyst who connects business strategy, digital experiences, customer behavior, and data to guide decisions. This role partners with senior leaders and cross-functional teams to frame ambiguous business needs as clear analytical problem statements, determine what must be measured, and identify creative, fact-based ways to answer the questions that matter most. The role owns the analytical lifecycle from data-first measurement design and tracking requirements through data collection, implementation support, quality assurance, exploratory analysis, metric development, dashboarding, and executive-ready storytelling.



ESSENTIAL FUNCTIONS of the ROLE

• Partner with leaders and cross-functional teams to understand business objectives, challenge assumptions, and translate ambiguous needs into clear analytical problem statements and measurable outcomes.
• Define the measurement strategy before implementation, including events, dimensions, metrics, data sources, tracking requirements, technical specifications, processes, and workflows.
• Serve as a trusted analytical advisor and lead consultant for senior stakeholders, guiding prioritization, measurement decisions, and resource alignment.
• Apply systems thinking to connect customer journeys, digital experiences, operational processes, source systems, and downstream reporting; identify dependencies, gaps, and creative approaches to answer business questions with evidence.
• Extract, transform and load data into database as required utilizing the most appropriate tool.
• Assess, produce and/or develop complex relevant, standard, or custom information (reports, dashboards, interactive reporting, charts, graphs and tables) from various data sources by querying data and generating the associated output. Distribute and disseminate analytical deliverables to applicable agencies, researchers, management and other customers.
• Lead end-to-end data quality assurance, including tracking validation, instrumentation QA, reconciliation, metric testing, anomaly detection, and documentation of known limitations before results reach leadership.
• Document project/work assignments to include all needed technical documentation such as source to target mappings, data sources, definitions, methodologies, contact information, output requirements or other information to ensure continuity of process.
• Interpret complex data and associated deliverables (reports, dashboards, interactive reporting, charts, graphs and tables) in plain business language for executive & clinical staff. Effectively summarize information and create intuitive/digestible information by selecting visualizations that are fit for purpose.
• Use advanced SQL to develop complex metrics, reusable analytical datasets, and exploratory data analyses that evaluate performance, explain drivers, test hypotheses, and surface opportunities across digital, customer, operational, and marketing use cases.
• Connect the dots across disparate data and perspectives to identify trends, root causes, opportunities, and risks; develop fact-based recommendations that leaders can act on.
• Provide technical mentorship and raise the team's analytical maturity through reusable methods, measurement standards, SQL practices, QA discipline, and clear storytelling.

KEY SUCCESS FACTORS

• Bachelor's degree in Statistics, Operations Research, Physics, Computer Science,
• Economics, Business, Clinical or other similar degree or equivalent experience required.
• Master's degree preferred.
• Strong analytical, systems-thinking, problem-solving, data manipulation, troubleshooting, and structured thinking skills, with the ability to decompose complex business problems into answerable analytical questions.
• Advanced development skills in the use of enterprise analytical and Bl tools, such as Cognos,
• Tableau, QIickView, Excel PowerPivot or SSRS.
• Advanced SQL skills, and comfort using Python, pyspark, including the ability to query, join, model, validate, and analyze complex data in Snowflake; develop sophisticated metrics and exploratory analyses; and optimize queries for repeatable use.
• Verbal and written communication skills.
• Ability to design and influence the implementation of measurement systems, tracking plans, and data pipelines necessary to collect, maintain, validate, and analyze trustworthy digital and business data.
• Ability to gather, integrate, and analyze data; define meaningful metrics; conduct exploratory analysis; and develop executive-ready reports and recommendations.
• Ability to work independently, lead cross-functional teams with minimal supervision, and influence decisions across product, marketing, technology, data engineering, and business functions.
• Knowledge of ETL & Data Warehousing.
• Ability to work with complex data of varying levels of quality and validity.
• Ability to develop data analytics and BI applications in a clear and understandable manner
• meeting user requirements.
• Inquisitive, hypothesis-driven mindset with the ability to learn new business domains, data sources, tools, and processes quickly; ask incisive questions; identify creative analytical approaches; and improve efficiency and decision quality.