Instructure

Sr. Data Engineer

Mexico full-time Mid Salary not listed
full-time Mid level Technology & IT Curated
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About the role

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 are looking for a Senior Data Engineer to lead the development and scaling of our core data infrastructure. You won’t just move data; you will be a key contributor in architecting and maintaining our Sources of Truth. Your mission is to transform raw, source data into authoritative, governed data marts by building high-performance pipelines and a robust Semantic Layer that ensures consistency across the entire business.

If you enjoy the challenge of orchestrating complex workflows utilizing Databricks, Fivetran, dbt, and Snowflake—and you take pride in ensuring key metrics are defined once and trusted everywhere—this is the role for you.

What You’ll Do

End-to-End Pipeline Engineering: Design, build, and deploy scalable ETL/ELT pipelines from diverse source systems into our Snowflake Data Cloud.

Cloud Infrastructure: Manage and optimize data flows within an AWS environment (S3, Lambda, IAM), ensuring high availability, security, and cost-efficiency.

High-Scale Processing: Leverage Databricks and Python (PySpark) to handle complex data transformations and high-volume workloads.

Implement the Semantic Layer: Collaborate with the team to define, implement, and scale our Semantic Layer (via dbt Semantic Layer, MetricFlow, or similar) to standardize business logic, metrics, and dimensions for all downstream consumers.

Model for Truth: Use dbt to build modular, version-controlled, and tested data models that serve as the definitive foundation for business intelligence.

Data Governance & Quality: Implement automated testing and monitoring to ensure the integrity and reliability of finished data marts.

Your Technical Toolkit

Data Warehousing: Expert-level proficiency in Snowflake (clustering, Snowpipe, streams, and tasks) or similar cloud data warehouses.

Analytics Engineering: Advanced mastery of dbt and complex SQL transformation logic, with specific experience building semantic models and metric definitions.

Big Data & Code: Strong Python skills and hands-on experience with Databricks for Spark-based orchestration.

Cloud Infrastructure: Practical experience managing data workloads within AWS.

Version Control: Deep understanding of Git-based workflows and CI/CD for data.

What you'll need to know/have:

A Data Quality Champion: You believe data is a liability until it’s governed, and you have a passion for data modeling and reducing "metric drift" across the organization.

Scale-Oriented & Efficient: You design for the long term, building streamlined, cohesive data environments that eliminate redundancy and fragmentation. By focusing on modular design and automation, you ensure our infrastructure is stable and easy to navigate as data complexity and volume grow.

A Problem Solver: You find the root cause of data discrepancies and build automated solutions to prevent them from recurring.

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.

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Mid
Technology & IT Data Analysis MySQL Python Remote Collaboration Sales Mid level

Likely questions

  1. Tell us about work you have done that is close to the Sr. Data Engineer role.
  2. How would you approach your first 30 days at Instructure?
  3. Which of Data Analysis, MySQL and Python have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with Data Analysis, MySQL and Python.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Sr. Data Engineer role because I can bring practical experience in Data Analysis, MySQL and Python, learn the team quickly, and contribute to the outcomes Instructure needs from this hire.

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