Sr Analytics Engineer - Customer Engineering

Our Company

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 Opportunity

We 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) Field 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 KPI 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 Do

• Create and maintain complex data models and queries to support cross-AEP analytics, dashboards, and self-serve tools
• Collaborate with stakeholders to understand business requirements and translate them into data insights reporting & analytics solutions
• Establish data modeling standards and patterns; ensure these models accurately measure KPIs, metrics, and supporting details.
• Build and maintain data pipelines and infrastructure for efficient data processing and analysis
• Collaborate with stakeholders to understand business requirements and translate them into technical solutions; enable and support stakeholders to access and analyze data effectively
• Optimize data processing and storage solutions for performance and cost efficiency
• Develop automated processes for data validation, cleaning, and transformation
• Implement data governance and quality standards; create documentation for data models, code, and standards
• Serve as a subject matter expert on data models and address questions quickly and accurately
• Approve data model changes as a reviewer and code owner for specific database schemas
• Integrate AI/ML models into data warehousing and analytics workflows
• Advocate for data quality programs and trusted data initiatives
• Lead major strategic data projects spanning six (6) months or more
• Lead, guide, and mentor junior team members to grow their skills and impact

What You Need to Succeed

The 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 acumen, 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 dynamic, internal start-up-oriented environment. Detailed list of desired skills is as follows:

Technical Skills

• Expert proficiency in SQL and data modeling.
• Proficiency in statistical programming languages like Python or R
• Experience 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 schemas

Business Acumen, Problem-Solving:

• Understanding of business processes, preferably in healthcare or related industries.
• Ability to collaborate with stakeholders and translate business requirements into technical solutions

• Strong analytical and problem-solving skills
• Ability to tackle complex problems from both technical and business perspectives.

Leadership, Communication:

• Experience managing or mentoring junior team members
• Planning, leading, and delivering data projects
• Excellent communication skills for presenting data insights to stakeholders
• Ability to create documentation, memos, and presentations

Additional Skills:

• Experience with data visualization tools like Tableau, Power BI
• Knowledge of data governance and quality standards
• Familiarity with AI/ML concepts and their application in analytics
• Familiarity with Adobe Experience Platform a major plus

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

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