Data Engineering Manager
Budapest
R&D – Engineering /
Full-time /
Hybrid
At Instructure, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers. We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:
We’re looking for a strong, hands-on Data Engineering Manager to lead a high-performing team responsible for the ingestion, transformation, and availability of large-scale data systems. This team is at the heart of our data platform, powering everything from customer-facing analytics to operational reporting. In this role, you’ll be responsible for managing engineers working across multiple systems and technologies—including Hudi, Iceberg, Spark, Kafka, Debezium, and SQL-based platforms. Experience with Snowflake is a plus, as we are currently migrating parts of our data stack. This is both a people leadership and technical role, where you’ll guide architectural decisions, mentor engineers, and ensure the reliability and scalability of our pipelines and platforms.
What you will be doing:
- Lead and grow a team of data engineers working on real-time and batch data processing.
- Oversee ingestion pipelines from PostgreSQL (via Debezium + Kafka/MSK) into Spark-based data lakes (Hudi/Iceberg).
- Support the team in building and optimizing Spark jobs and workflows for large-scale data processing.
- Provide technical leadership on data lake architecture, schema evolution, and data quality practices.
- Collaborate with other engineering and product teams to ensure reliable data availability for key use cases.
- Work closely with platform leadership to evolve the architecture, including a transition toward Snowflake.
- Own team delivery, sprint planning, and performance management.
- Create a culture of accountability, mentorship, and continuous improvement.
What you will need to know/have:
- 3+ years of experience managing data engineering or platform teams.
- Strong technical background with 5+ years in data engineering or related fields.
- Hands-on experience with at least several of the following: Hudi, Iceberg, Apache Spark, Apache Kafka, Debezium, PostgreSQL, AWS S3.
- Proficient in SQL and Python or Scala for data workflows.
- Comfortable navigating hybrid cloud/on-prem environments and modern data architectures.
- Strong communication and leadership skills, with a focus on enabling team success and technical excellence.
- Experience working across time zones and distributed teams.
It would be a bonus if you had:
- Experience with Snowflake, dbt, or other cloud data warehouses.
- Familiarity with data governance, access control, or metadata management.
- Experience working in an organization undergoing data platform modernization or cloud migration.
Get in on all the awesome at Instructure!
- We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:
- Competitive compensation and participation in Instructure’s equity program
- Flexible schedules and a remote-friendly culture, with hybrid or onsite work based on business needs
- Annual “Dim the Lights” company-wide shutdown from December 26 to December 31
- Comprehensive wellness programs and mental health support
- Annual learning and development stipends to support your growth
- We provide the technology and tools you need to do your best work—typically a Mac, with PC options available in some locations
- A culture rooted in inclusivity, support, and meaningful connection
We’ve always believed in hiring the most awesome people and treating them right. We know that the more diverse we are, the more diverse our ideas will be and when we openly welcome those ideas, our environment is better and our business is stronger.
All Instructure employees are required to successfully pass a background check upon being hired.
