Skill needed: Python, Machine Learning.
Employer: Dynatrace
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:Data Product Design & DevelopmentDesign and develop scalable analytical data models, curated datasets, conformed dimensions, and standardized metricsTranslate complex business requirements into clear, reliable, and reusable data products that support both executive reporting and day-to-day analytics use casesContribute to designing data models and metadata structures with AI readiness in mind, including column-level descriptions, consistent naming conventions, and well-documented semantic contextBuild and maintain data structures that support discoverability and usability across analytics, BI, and emerging AI/ML use casesStandards, Quality & GovernanceFollow and contribute to established standards and best practices for SQL development, dbt modeling, testing, documentation, and data qualitySupport the implementation of the semantic layer by ensuring metric definitions and business logic are consistently appliedImplement and maintain data quality checks, governance standards, and security measures within dbt models and SnowflakeHelp ensure data models are well-tested, documented, and aligned with business definitionsCollaboration & Technical ContributionPartner with data engineers, platform teams, governance, and business stakeholders to gather requirements and deliver data solutionsCollaborate with team members through code reviews, knowledge sharing, and adoption of best practicesContribute to cross-functional initiatives focused on improving standardization, consistency, and reuse of analytics assetsIdentify opportunities to improve processes, enhance automation, and streamline development workflowsWhat will help you succeedRequiredBachelor’s degree in Computer Science, Information Systems, Engineering, or a related field5–8+ years of experience in analytics engineering, data modeling, or related roles with strong focus on SQL programmingStrong SQL skills, including experience with complex analytical queries and performance optimizationSolid hands-on experience with dbt Cloud, including models, tests, and documentation practicesExperience working with Snowflake, including query tuning and understanding of warehouse performanceStrong understanding of dimensional modeling (Kimball) concepts including star schemas, conformed dimensions, and slowly changing dimensionsExperience working within established analytics engineering or data modeling frameworks and standardsAbility to work independently on complex tasks while collaborating effectively with cross-functional teamsStrong communication skills, with the ability to translate technical concepts for business stakeholdersExperience with data quality validation, testing approaches, and governance alignmentProficiency with Git/GitHub workflows including pull requests and code reviewsProven 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 neededPreferredMaster’s degree in a related fieldPython experience for automation, scripting, or data validationExposure 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 casesExperience with data ingestion tools such as FivetranExposure to enterprise systems such as Salesforce, NetSuite, or SuccessFactorsWhy you will love being a DynatracerDynatrace 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.