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Senior Software Engineer, Data

Budapest, Hungary · Budapest, Central Hungary, Hungary

Live, first seen by us 72 days ago
Pay
Pay not listed
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Research & Development › Engineering — team source
Department: Research & Development › Engineering
From the employer’s posting

What you’ll work on

Full 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

From the employer’s posting
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

What you’ll bring

All qualifications

Core experience

  • 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)
Qualification wording
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)
Apply at Instructure

Posting record

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Status in our records
Live
First seen by us
Aug 24, 202672 days ago
Recorded sightings
75
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

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.

Instructure is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

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.

  • Python
  • SQL
  • AWS
Where the posting names them
- 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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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 839, the most 1,314, and the latest week had 1,086.
August 17Last week

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.

About the role

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.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

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.

What You'll Do

  • 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

What You'll Need

  • 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

It Would Be a Bonus If You Had

  • 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.

 

Why Join Us

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.

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Pay

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Location & working pattern

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.
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