Sr Analytics Engineer - Customer Engineering

Our CompanySkills, Experience, Qualifications, If you have the right match for this opportunity, then make sure to apply today.Changing the world through digital experiences is what Adobe's all about. We give everyone"”from emerging artists to global brands"”everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!The OpportunityWe seek a senior, experienced "˜hands-on' analytics engineer to join our Customer Engineering team within the Adobe Digital Experience (DX) Cloud Engineering. Customer Engineering (CE) focuses on multiple aspects of product experience for Adobe Experience Platform (AEP) and AEP-related Apps, including diagnostics and prevention of customer issues and technical enablement to help customers quickly and iteratively move through the product adoption lifecycle to realize business value. The CE team also partners closely with our Adobe Field teams (Pre-Sales, Consulting, and Support) and 3rd party partners to collect and synthesize real-world customer patterns to align our product roadmap and develop technical frameworks and tooling to help these field teams achieve scale and impact as they engage with customers.As our AEP business grows, our product and broader engineering teams are challenged to scale themselves to meet the customer and field team demands. In particular, various teams need data-driven, actionable insights that help identify, prioritize, and focus people and technology investments to help customers struggling to run, operate, or grow business impact from their AEP E2E system. In addition, there is ample opportunity to infuse more customer self-serve intelligence into our products through reporting, analytics, and even AI assistance. This senior analytics engineer would be one of the founding members of a Customer Data Science & Analytics team to take on these challenges - requiring this person to model and deliver critical data sets that support new cross-product & engineering critical metric reporting, predictive intelligence (e.g., at-risk customers, customer maturity, etc.), and in-product usage and value frameworks. This role will collaborate closely with data science colleagues and other internal cross-team data engineers, ML ops, and decision science platform teams.What You'll DoCreate and maintain complex data models and queries to support cross-AEP analytics, dashboards, and self-serve toolsCollaborate with partners to understand business requirements and translate them into data insights reporting & analytics solutionsEstablish data modeling standards and patterns; ensure these models accurately measure metrics, and supporting details.Build and maintain data pipelines and infrastructure for efficient data processing and analysisCollaborate with partners to understand business requirements and translate them into technical solutions; enable and support partners to access and analyze data effectivelyOptimize data processing and storage solutions for performance and cost efficiencyDevelop automated processes for data validation, cleaning, and transformationImplement data governance and quality standards; document for data models, code, and standardsServe as a domain expert on data models and address questions quickly and accuratelyApprove data model changes as a reviewer and code owner for specific database schemasIntegrate AI/ML models into data warehousing and analytics workflowsAdvocate for data quality programs and trusted data initiativesLead major strategic data projects spanning six (6) months or moreLead, guide, and mentor junior team members to grow their skills and impactWhat You Need to SucceedThe optimal candidate will have 5-7+ years' experience in analytics engineering or related data engineering roles, including a unique blend of technical data skills, business sense, and the ability to communicate complex data concepts to technical and non-technical audiences. They should be able to work independently and as part of a team in a multifaceted, internal start-up-oriented environment. Detailed list of desired skills is as follows:Technical SkillsExpert proficiency in SQL and data modeling.Proficiency in statistical programming languages like Python or RExperience with data warehousing technologies and cloud platforms (e.g., AWS, Azure)Expertise in analytics and data engineering concepts, tools, and technologies.Proficiency in data transformation tools like dbt (data build tool)Experience with data orchestration platforms (e.g., Airflow, Glue)Knowledge of dimensional modeling and star/snowflake schemasBusiness Insight, Problem-Solving:Understanding of business processes, preferably in healthcare or related industries.Ability to collaborate with partners and translate business requirements into technical solutionsStrong analytical and problem-solving skillsAbility to tackle complex problems from both technical and business perspectives.Leadership, Communication:Experience managing or mentoring junior team membersPlanning, leading, and delivering data projectsGood interpersonal skills for communicating data insights to partnersAbility to document, memos, and presentationsAdditional Skills:Experience with data visualization tools like Tableau, Power BIKnowledge of data governance and quality standardsFamiliarity with AI/ML concepts and their application in analyticsFamiliarity with Adobe Experience Platform a major plus#J-18808-Ljbffr

Created: 2024-11-11