Dynatrace’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:
- 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
- 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
- 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
- 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
- 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
- Dynatrace is a leader in unified observability and security.
- We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance.
- Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances.
- You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically.
- Over 50% of the Fortune 100 companies are current customers of Dynatrace.
Due to legal reasons we are obliged to disclose the minimum salary for this position, which is €61,000 gross per year based on full-time employment (38.5 h / week). We offer a higher salary in line with qualifications and experience.
DynatraceWienYou will work closely with business stakeholders, data engineers, platform engineers, and BI teams to develop trusted, scalable, and well-governed datasets.…21d
SnapWienLead or participate in the design, architecture and implementation of embedded software in both prototype and shipping consumer products.…30d+
InnioJenbachWork on several projects simultaneously, under the supervision and guidance of senior engineers and managers. Good connections to public transport - station in……27d