Time since we first saw it
Day 72
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 11,035 similar postings that came down. Coming down is not always a hire.
Budapest, Hungary · Budapest, Central Hungary, Hungary
Live, first seen by us 72 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Research & Development › EngineeringFrom the employer’s posting
Own data models and storage across relational, graph, and retrieval data
Build APIs, backend services, and pipelines that keep data current
Design ingestion and update workflows with incremental processing and safe backfills
Own data correctness, query performance, and scalability
Diagnose production issues and improve reliability and observability
Own the data models and storage architecture behind our AI systems, across relational, graph, and retrieval-oriented data
Build and operate the APIs, backend services, and pipelines that keep that data current and accessible
Design reliable ingestion and update workflows, including incremental processing, schema changes, and safe backfills
Own data correctness, query performance, and scalability as volume and complexity grow
Diagnose production issues and improve reliability, observability, and operational efficiency
Deep experience with relational data systems and strong judgment about when graph or other specialized databases are the right choice
Deep experience operating a graph database in production, including traversal performance and query tuning at scale
Experience building reliable ingestion and update pipelines, including incremental processing, data-quality checks, schema changes, and safe backfills
Experience with versioned, bitemporal, or event-sourced data systems
Experience designing production services with clear API contracts, versioning, error handling, and performance considerations
Experience with vector search or semantic retrieval components (pgvector, OpenSearch, Pinecone, or similar)
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 72
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 11,035 similar postings that came down. Coming down is not always a hire.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Six or more years of experience building and operating production backend, data, or distributed systems - Strong production Python and SQL, including experience building APIs, designing schemas, optimizing queries, and working with large or complex datasets - Deep experience with relational data systems and strong judgment about when graph or other specialized databases are the right choice
- Experience designing production services with clear API contracts, versioning, error handling, and performance considerations - Hands-on experience deploying and operating services in AWS using containers, CI/CD, monitoring, and production debugging tools - Strong engineering practices around testing, code review, observability, documentation, and maintaining systems that other teams depend on
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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:
Our AI team is where a lot of that gets built: applying advanced AI to real problems in learning, and turning research into product capabilities that educators and students use every day.
We're building the data platform behind our AI features: the models, pipelines, and services that hold the data those features depend on. This role owns it in production.
You’ll design the data models, build the services and pipelines that keep them current, and ensure they remain reliable as usage and complexity grow. This is backend and data engineering for systems where getting the structure of the data right is the core challenge.
You'll work alongside data scientists and applied AI engineers who build on what you own, and with our infrastructure team on deployment and operations.
Own the data models and storage architecture behind our AI systems, across relational, graph, and retrieval-oriented data
Build and operate the APIs, backend services, and pipelines that keep that data current and accessible
Design reliable ingestion and update workflows, including incremental processing, schema changes, and safe backfills
Own data correctness, query performance, and scalability as volume and complexity grow
Turn prototypes into production-ready data services, scoring workflows, and retrieval components
Diagnose production issues and improve reliability, observability, and operational efficiency
Six or more years of experience building and operating production backend, data, or distributed systems
Strong production Python and SQL, including experience building APIs, designing schemas, optimizing queries, and working with large or complex datasets
Deep experience with relational data systems and strong judgment about when graph or other specialized databases are the right choice
Experience building reliable ingestion and update pipelines, including incremental processing, data-quality checks, schema changes, and safe backfills
Experience designing production services with clear API contracts, versioning, error handling, and performance considerations
Hands-on experience deploying and operating services in AWS using containers, CI/CD, monitoring, and production debugging tools
Strong engineering practices around testing, code review, observability, documentation, and maintaining systems that other teams depend on
Deep experience operating a graph database in production, including traversal performance and query tuning at scale
Experience with versioned, bitemporal, or event-sourced data systems
Experience with vector search or semantic retrieval components (pgvector, OpenSearch, Pinecone, or similar)
Experience with multi-tenant data design and per-tenant isolation
Onsite Collaboration Requirement: This role requires working onsite on Tuesday and Wednesday, with Thursday strongly encouraged as part of our company’s in-person collaboration model.
Join us and help shape the future of education by turning cutting-edge AI into reliable product capabilities.
At Instructure, we're on a mission to help educators and students learn together, anytime, anywhere, and however works best. You'll join our research-driven team tackling education's biggest challenges with cutting-edge technology.
We value diversity, creativity, and passion, and invest in our teams through mentorship, hack weeks, internal conferences, and a culture where innovation thrives. Here, you'll have the chance to build the next generation of LMS features that make a real impact on students and teachers, and do it in a collaborative, supportive environment that encourages experimentation and growth.
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, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.
Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.
Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.
Comprehensive wellness programs and mental health support
Learning and development resources, including professional development tools and tuition reimbursement, to support your growth
The technology and tools you need to do your best work
Motivosity employee recognition program
A culture rooted in inclusivity, support, and meaningful connection
We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.
Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.
All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.
Any attempt to misrepresent personal or professional information will result in disqualification.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Budapest, Central Hungary, Hungary
- Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success. - Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location. - Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.
No clear work-authorization passage found. Eligibility is unconfirmed.