Dynatrace provides software intelligence to simplify cloud complexity and accelerate digital transformation. With automatic and intelligent observability at scale, our all-in-one platform delivers precise answers about the performance and security of applications, the underlying infrastructure, and the experience of all users to enable organizations to innovate faster, collaborate more efficiently, and deliver more value with dramatically less effort. That’s why many of the world’s largest organizations trust Dynatrace®️ to modernize and automate cloud operations, release better software faster, and deliver unrivalled digital experiences.
Our Business Intelligence R&D team in D1 is looking for an experienced for a Senior Data Engineer to design and build data pipelines that ingest, transform, and serve data from an observability platform into analytics, applications, and data science workflows.
This role sits at the intersection of telemetry data, analytical platforms, and product data consumption. You will work closely with application teams, data scientists, and platform engineers to ensure data is reliable, well modeled, and ready to be used across multiple purposes, from near real time insights to exploratory analysis and reporting.
Minimum skillset:
At least five years of experience in Data Engineering (ideally applied to BI systems).
Strong proficiency in SQL and Python, with experience building and operating production data pipelines.
Proven ability to optimize data pipelines supporting real‑time or client‑facing applications (dashboards, reporting, or data‑driven features).
Be comfortable operating in crossfunctional environments and translating business or product needs into concrete data structures.
Desriable skillset:
Ability to deal with ambiguity, prioritize effectively, and deliver results in a dynamic environment.
Degree in Engineering, Computer Science, Mathematics, or another quantitative field.
Hands‑on experience with modern analytics platforms, such as Snowflake (data modeling, transformations, performance tuning).
Experience supporting analytics, data science, or data driven applications through SQL, notebooks, or programmatic data access.