• Independently triage and resolve pipeline data quality issues • Author at least one new dbt model or refactor an existing one to meet current modeling standards • Design a dbt test suite for a set of models lacking coverage • Understand the end-to-end pipeline from ingress through silver and gold, and be able to trace a data quality issue to its root layer • Building strong working relationships with clients and cross-functional partners (Data Engineering, Customer Success) • Deeply familiar with Arcadia's full data stack — from ingress through silver, gold, and downstream consumers • Driving at least one improvement project forward, whether technical (e.g. model refactor, new DQ framework) or process-focused (e.g. promotion playbook, triage workflow) • Recognized as a leader within the department — peers and stakeholders seek out your expertise on data modeling and quality • Operating independently across the full scope of the role with minimal guidance • Two or more improvement projects completed and in production, with measurable impact on data quality or operational efficiency

• Engage with both internal and external customers • Solve unique data challenges and provide creative solutions • Develop custom solutions to help clients fully engage with our platform and services • Manage incoming communications through phone calls, emails, team chats, and Jira tickets • Provide accurate, valid and complete information using the right methods/tools • Follow up with clients to check satisfaction and success with solutions • Handle customer complaints, provide appropriate solutions and follow up for resolution • Troubleshoot common platform issues

• Own the data architecture for one of our products, designing, building, and continuously evolving ETL/ELT pipelines as the product and its data model change rapidly; • Support customer-facing work: data requests, POCs, and analyses that directly influence commercial outcomes; • Drive data quality and architecture decisions independently, this role requires judgment, not just execution; • Develop HTML-based dashboards and visualizations that surface the metrics and funnel visibility the product and business teams need to act; • Build and maintain data endpoints consumed by React-based product pages, stepping into front-end development when needed because you can and it moves things faster; • Bring genuine AI fluency to your workflow, not as a buzzword, but as a way of working; we’ll ask you how you’d use AI to improve what you’re building, and we expect a real answer.

Your role at DynatraceDynatrace’s Data & Analytics organization is focused on building a scalable, AI-ready, self-service data ecosystem across the company. As a Senior Analytics Engineer, you will play a key role in designing and delivering high-quality data products that support reporting, self-service analytics, and emerging AI use cases. This is a hands-on technical role for someone who excels at translating business needs into well-structured, reliable analytical data assets. You will work closely with business stakeholders, data engineers, platform engineers, and BI teams to develop trusted, scalable, and well-governed datasets. In addition, you bring awareness of modern AI-assisted development workflows, including tools such as GitHub Copilot or Claude, and are comfortable leveraging these to improve productivity, documentation, and data model design. You will contribute to advancing our data modeling practices and help ensure that our data products are consistent, reusable, and aligned with business goals. Key Responsibilities: Data Product Design & Development - Design and develop scalable analytical data models, curated datasets, conformed dimensions, and standardized metrics - Translate complex business requirements into clear, reliable, and reusable data products that support both executive reporting and day-to-day analytics use cases - Contribute to designing data models and metadata structures with AI readiness in mind, including column-level descriptions, consistent naming conventions, and well-documented semantic context - Build and maintain data structures that support discoverability and usability across analytics, BI, and emerging AI/ML use cases Standards, Quality & Governance - Follow and contribute to established standards and best practices for SQL development, dbt modeling, testing, documentation, and data quality - Support the implementation of the semantic layer by ensuring metric definitions and business logic are consistently applied - Implement and maintain data quality checks, governance standards, and security measures within dbt models and Snowflake - Help ensure data models are well-tested, documented, and aligned with business definitions Collaboration & Technical Contribution - Partner with data engineers, platform teams, governance, and business stakeholders to gather requirements and deliver data solutions - Collaborate with team members through code reviews, knowledge sharing, and adoption of best practices - Contribute to cross-functional initiatives focused on improving standardization, consistency, and reuse of analytics assets - Identify opportunities to improve processes, enhance automation, and streamline development workflows What will help you succeedRequired - Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field - 5–8+ years of experience in analytics engineering, data modeling, or related roles with strong focus on SQL programming - Strong SQL skills, including experience with complex analytical queries and performance optimization - Solid hands-on experience with dbt Cloud, including models, tests, and documentation practices - Experience working with Snowflake, including query tuning and understanding of warehouse performance - Strong understanding of dimensional modeling (Kimball) concepts including star schemas, conformed dimensions, and slowly changing dimensions - Experience working within established analytics engineering or data modeling frameworks and standards - Ability to work independently on complex tasks while collaborating effectively with cross-functional teams - Strong communication skills, with the ability to translate technical concepts for business stakeholders - Experience with data quality validation, testing approaches, and governance alignment - Proficiency with Git/GitHub workflows including pull requests and code reviews - Proven experience with AI-assisted development tools such as GitHub Copilot, Claude, or similar, and the ability to leverage them to improve productivity, development workflows, and documentation. - Experience or familiarity with Power BI, including understanding of downstream reporting needs and the ability to support or contribute to BI development when needed Preferred - Master’s degree in a related field - Python experience for automation, scripting, or data validation - Exposure to semantic layer concepts or metric frameworks (e.g., dbt Semantic Layer, Cube, AtScale) - Familiarity with AI/ML data readiness, feature engineering concepts, or designing data for downstream advanced analytics use cases - Experience with data ingestion tools such as Fivetran - Exposure to enterprise systems such as Salesforce, NetSuite, or SuccessFactors Why you will love being a Dynatracer - A one-product software company creating real value for the largest enterprises and millions of end customers globally, striving for a world where software works perfectly. - Working with the latest technologies and at the forefront of innovation in tech on scale; but also, in other areas like marketing, design, or research. - A team that thinks outside the box, welcomes unconventional ideas, and pushes boundaries. - An environment that fosters innovation, enables creative collaboration, and allows you to grow. - A globally unique and tailor-made career development program recognizing your potential, promoting your strengths, and supporting you in achieving your career goals. - A truly international mindset with Dynatracers from different countries & cultures all over the world, and English as the corporate language that connects us all - A culture that is being shaped by the diverse personalities, expertise, and backgrounds of our global team. Compensation and Rewards