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

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

Role Description Analytics Engineers at CookUnity are data product owners who sit in a single team on a mission to minimize time spent by analysts and data scientists discovering, understanding, and preparing data before launching into their work. Each analytics engineer has ownership and autonomy over a set of entities/tables in a domain, collaborating on a single data design from first principles that the team owns together. As their products mature, they merchandise them as Tableau Connections, extracts into sheets, or any other endpoint needed to achieve their mission. Some analytics engineers have an interest in data infrastructure and integrations, others in bringing their data to life through interactive visualizations, but all have the skills to work with unruly raw data, design analytics-friendly data products (including entities and flat tables), and build them to a production standard that the whole company can rely on. Everyone in data at CookUnity comes with a high agency mindset, a passion for collaborating with others, a pattern of achievement, and a sincere interest in investing in their own development. Responsibilities - Own Core Data Products - Design, build, and maintain dbt models in Snowflake that reflect key business logic and serve as reliable sources of truth. Define clear ownership, usage expectations, and roadmaps for your data products. - Build Trustworthy, Scalable Models - Develop models that are easy to use, tested, documented, and serve a wide range of stakeholders. Measure success through usage metrics, reduced support needs, and SLA coverage. - Ensure Reliability and Observability - Monitor pipelines, track schema changes, and implement testing and alerting to ensure consistent data quality and uptime. - Drive Iteration Through Feedback - Collect and act on feedback from users. Use metrics, interviews, and usage logs to continuously improve your data products and documentation. - Advance AI Adoption in Analytics - Champion the use of agentic and AI-assisted tools in data workflows. Lead pilots, measure impact, and scale successful practices across the team. - Collaborate Cross-Functionally - Work with Engineering, Product, and Ops to align on metrics, instrumentation, experimentation, and data needs. - Mentor and Raise the Bar - Review code, guide design decisions, and share knowledge to elevate the craft of Analytics Engineering within the team. Qualifications - 4+ years of experience in Analytics Engineering, Data Engineering, or a similar role working with modern data stacks (dbt, Fivetran/Airbyte, Airflow, Snowflake/BigQuery, etc.) - Deep understanding of data modeling principles (e.g. dimensional modeling, ELT best practices, testing strategies, etc.) - Proficiency in SQL and version control (Git), with experience shipping production-quality data pipelines - Experience collaborating closely with cross-functional stakeholders (Product, Engineering, Operations, etc.) to translate business needs into data solutions - Comfort navigating ambiguity in fast-paced environments, with a strong sense of ownership and problem-solving mindset - Familiarity with BI tools (e.g. Tableau, Hex, Looker) and a passion for enabling self-serve data culture - Excellent communication skills, with the ability to explain technical concepts to non-technical audiences Benefits - 💸 Get paid in USD - 🗺 Work remotely: design the life that you want - ⛱ Enjoy 15 days of vacation each year from the start date - 🎄 16 fully paid Argentinean holidays - 🩺 Healthcare Benefit: Monthly stipend to use in your preferred healthcare provider - 🗓️ 5-year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical - 🐣 Paid Family leave - 🕯 Compassionate Leave: 3-5 days each time the need arises - 🧘🏽‍♀️ Customize the benefits that suit your needs! Access a range of perks tailored to you, including learning opportunities, wellness memberships, delivery apps, and more through our comprehensive benefit platform - 🧑‍🏫 Personalized English coach

Role Description At Oversee, we are reimagining how corporate travel is managed. Our advanced technology and machine learning eliminate outdated, manual processes that hold companies back - driving cost savings, improving efficiency, and enabling smarter decision-making. We combine travel analytics with actionable insights, giving global enterprises the tools to gain visibility into their travel spend while continuously optimizing their programs. In this role, you’ll have meaningful influence over data architecture, tooling, and how AI is embedded into internal workflows and product development. It’s a strong fit for someone who enjoys solving complex data problems, working closely with product and engineering, and building systems that directly impact the business. What you’ll do: - 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. - Bring genuine AI fluency to your workflow; we’ll ask you how you’d use AI to improve what you’re building, and we expect a real answer. Qualifications - 5+ years in analytics engineering, data engineering, or a closely related role - with strong, proven data modeling and ETL/ELT experience. - Python is a must; you use it regularly and confidently for transformation, automation, or analysis. - Strong SQL and a solid grasp of data warehouse architecture; hands-on experience with Snowflake or dbt is a significant plus. - Senior-level independence; you can own ambiguous problems, make architecture calls, and communicate tradeoffs clearly to non-technical stakeholders. - An active and thoughtful AI user; you have a real point of view on how AI changes data work, and you back it up with how you actually operate day-to-day. - Comfortable contributing to front-end layers or working directly alongside React engineers without friction. - Strong analytical mindset - business-oriented, funnel-aware, and able to go from raw data to insight without being handed the question first. - BS in Computer Science, Statistics, Industrial Engineering, or a related quantitative field preferred. Requirements - Data warehouse: Snowflake, Dbt - Analytics & Visualization: Power BI - Languages: SQL, Python - Data orchestrator: Dagster Benefits - Dynamic, fast-paced, and positive environment. - Opportunity to solve a $17B global problem. - Exponential YoY revenue growth. - Partnerships with some of the world’s largest Fortune 500 companies. Company Description We are proud to be an equal opportunity workplace. We provide employment opportunities without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or veteran status.