Role Description
As an Infrastructure Software Engineer on the Data Observability team, you will build and operate foundational systems that ensure the reliability, visibility, and governance of analytical data across Dropbox. This role is critical to maintaining trust in our data, enabling teams to ship features, understand product usage, and optimize performance with confidence.
You will work on data platform that supports analytics and machine learning pipelines at scale, with a focus on data quality monitoring, metadata management, and governance enforcement. Your work will help prevent data errors, reduce outages, and close compliance gaps across some of the largest and most complex data systems at Dropbox.
Partnering closely with engineers, data scientists, and product teams, you will tackle complex technical challenges and influence how data is produced, monitored, and consumed across the company. Your contributions will directly impact teams across Dropbox and help shape the future of how we manage and operate data at scale.
This is a foundational infrastructure role for engineers who are passionate about building scalable, reliable systems that power mission critical products and enable the next generation of data driven innovation.
Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.
Responsibilities
Designing, implementing, and maintaining scalable data platform components to support analytics, governance, and AI/ML workloads across the enterprise.
Collaborating closely with data engineering, data science, and ML teams to ensure data reliability and observability.
Supporting data quality monitoring such as anomaly detection, freshness, and schema validation.
Managing metadata including ownership, documentation, and classification.
Enforcing compliance through retention policies and data contracts.
Contributing to platform modernization and adoption of cutting-edge data tools.
Supporting the reduction of data errors, outages, and compliance gaps to enable confident data-driven decisions.
On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.
Requirements
2+ years of experience in data engineering, platform engineering, or software engineering roles.
A BS degree in Computer Science or a related technical field, or equivalent experience.
Proven success in developing and deploying large-scale data pipelines or platforms focused on quality, governance, and reliability.
Proficiency in building and maintaining ETL/ELT workflows, APIs, and integrations with cloud-based data systems.
Ability to deliver end-to-end data platform features efficiently.
Willingness to participate in on-call rotations if required by the team.
Preferred Qualifications
Experience with Databricks, Delta Lake, Snowflake or similar big data platforms.
Experience with DataOps.
Programming experience in Python and SQL.
CompensationPoland Pay Range212 500 zł—287 500 zł PLN