Data Analyst 2

Contract to Hire/ Temp to Perm Day to Day Responsibilities Segment Design, Build & Activation Design, build, and manage audience segments in Salesforce Data Cloud across members, brokers, employers, prospects, and other persona targets — including identity‑resolved audiences, computed traits, calculated insights, and predictive score‑based segments Translate business requirements from Marketing, Digital, Sales, Broker Engagement, Employer Engagement, and clinical engagement partners into precise, reusable segment definitions that align with the unified data model (Member 360, 590 attributes, 12 data domains) and consent/compliance requirements Build and configure segment logic using multi‑rule, cross‑object criteria — e.g., eligibility status, LOB, care program enrollment, outreach status, member engagement data, care gaps, pharmacy claims, and other data attributes available in Data Cloud Activate segments into downstream platforms including Marketing Cloud Engagement (MCE) for email/SMS/push journeys and Marketing Cloud Personalization (MCP) for real‑time web/mobile Create and maintain common (reusable) segments scheduled on a daily cadence to keep data sets ready for ad hoc and campaign‑specific segment requests, reducing build time from weeks to days Build campaign‑specific segments on top of common segments for individual use cases such as care management, complex care, Medi‑Cal redetermination, diabetes management, gaps in care, and member onboarding Segmentation Governance & Taxonomy Establish and enforce segmentation taxonomy, naming standards, reuse patterns, and audience lifecycle governance (create → optimize → retire) to reduce duplication, maintain auditability, and improve activation throughput across business domains Manage the segment review and deployment process — build segments in non‑production (Dev/QA), conduct design reviews and code reviews, validate credit consumption and segment complexity, and coordinate release to production through the established change management process Monitor and manage Data Cloud credit consumption related to segmentation activity — review segment complexity before deployment to prevent overconsumption and flag duplicate or redundant segments Restrict and govern production access — ensure business users have read/query access to data model objects for reporting but do not create or modify segments directly in production; only reviewed and approved segments are promoted Intake, Backlog & Operational Workflow Operate the daily segmentation backlog — intake, prioritization, build, QA, and activation — partnering with campaign operations, BSAs, and personalization engineering to ensure audiences are delivered on time and at quality Participate in JIRA‑based intake workflow — receive segment requests via JIRA intake templates, collaborate with BSAs (e.g., Noelle Locati Acosta) on triage, and participate in weekly reviews with project managers and operations to assess data requirements and progress Conduct data analysis to determine whether required data attributes exist in Data Cloud, identify gaps, and coordinate with data engineering when new data sources or attributes are needed (e.g., claims history, program enrollment, care gaps, interaction history) Adhere to weekly cadence for standard segment deployments, with urgent needs fast‑tracked through an expedited review path Data Analysis & Requirements Translation Analyze source data within the Data Cloud unified data model to validate segment logic against complex data structures with multiple identity types and source systems Develop and validate calculated insights — derived fields such as days_until_renewal, redetermination_flag, propensity scores, and other computed metrics used as segment criteria Write, read, and debug SQL and segment logic to ensure segment accuracy and performance against the unified data model Document business rules, segmentation logic, and data requirements for each use case — including data sources, eligibility rules, outreach‑specific rules, and audience definitions — maintained as epics and stories in JIRA/Confluence Cross‑Functional Collaboration Partner daily with Product Managers (Data Cloud and SFMC leads) to align segment builds with roadmap priorities, platform releases, and activation requirements Collaborate with Marketing Operations, Digital, and clinical teams to understand campaign objectives, success metrics, and channel‑specific requirements (email, SMS, member portal, CareConnect, Pega CRM) Work with platform administrators and developers (Stellarus KLO resources) on segment deployment, environment management, permission sets, and production release alignment Coordinate with data engineering and architecture teams when new data ingestion, data stream mapping, or zero‑copy federated data connections are required to support segment criteria Support analytics and reporting needs — partner with analytics teams to ensure segment data is accessible for marketing attribution, campaign performance measurement, and CJA reporting Documentation & Enablement Create and maintain technical documentation — audience standards, reusable segmentation patterns, operational SOPs, and playbooks that allow the segmentation capability to scale across business domains without re‑engineering Educate business stakeholders on Data Cloud segmentation capabilities, self‑service query access, and the intake process for requesting new segments Serve as segmentation SME to cross‑functional teams — provide guidance on what is feasible within the current data model, recommend segment design approaches, and advise on complexity/effort using the team’s T‑shirt sizing framework (XS through XXL) Platform Operations & Quality Perform QA and validation on all segments before production activation — verify audience counts, logic accuracy, data freshness, and downstream activation contracts Monitor segment performance and refresh cadence — ensure segments are refreshing on schedule and activation targets are receiving updated audiences as expected Support environment strategy — use production or staging environments for data analysis, build segments in Dev, and follow the established SDLC for promotion through QA → Staging → Production Identify and flag risks — proactively surface issues such as complex nested segments, credit overconsumption, duplicate audiences, and data quality gaps to Product Management Required Skills (top 3 non‑negotiables) Agile Experience – 2 Years minimum Data Analytics – 3–5 years Data Strategy – 3–5 years Data Segmentation – 3–5 years Preferred Skills (nice to have) Salesforce Data Cloud Salesforce Marketing Cloud Snowflake Additional Requirements No hands‑on experience with Salesforce Data Cloud (CDP) or comparable enterprise CDP platforms — purely marketing ops or campaign execution backgrounds without data modeling/segmentation depth No demonstrated ability to write or debug SQL — candidates who are exclusively drag‑and‑drop or GUI‑only without query‑level data analysis skills Bachelor’s degree in Data Analytics, Information Systems, Computer Science, Marketing Analytics, or related quantitative field Equivalent professional experience (4 years) in CDP/data platform segmentation accepted in lieu of degree Scenario‑based segment build exercise — given a business use case and sample data model, candidate must walk through how they would design, build, and validate an audience segment SQL proficiency assessment — ability to read, write, and troubleshoot queries against a multi‑object relational data model SQL, Tableau, Adobe Journey Optimizer, Adobe Analytics, Google Analytics, or similar analytics tools/tech Salesforce Data Cloud Accredited Professional (or obtained within 90 days of start) Salesforce Marketing Cloud Email Specialist or Administrator certification (preferred, not hard requirement if strong CDP experience exists) #J-18808-Ljbffr