[Remote] Data Engineer at Top Hat

Canada

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Education Technology, Higher EducationIndustries

Requirements

3+ years of data engineering experience building production-grade pipelines and data assets
Solid intermediate understanding of layered/medallion architectures and entity modelling (data modelling)
Strong proficiency in SQL query tuning and optimization
3-4 years of ETL/ELT development using Python (or Scala) for production-grade transformations
Hands-on experience with at least one or multiple cloud platforms (AWS, GCP, or Azure)
Practical experience with lakehouse/warehouse technologies such as Athena, Redshift, BigQuery, Snowflake, or Databricks
3+ years using pipeline orchestration frameworks (e.g., Airflow, MWAA, Dagster) and familiarity with CI/CD pipelines for deployment
Working familiarity and optimization with structured and semi-structured data (e.g., JSON, Avro, Parquet)
Proven experience implementing data quality, governance, access controls, and PII handling (senior level)
1–2 years experience with graph databases, modelling, and query optimization (e.g., Neo4j)
2–3 years experience with event-driven architectures

Responsibilities

Design and model data: Build and optimize BI-oriented dimensional models (star/snowflake) and ER data models supporting analytics and product use cases in a layered (medallion-style) architecture
Build pipelines: Develop and maintain reliable, scalable ETL/ELT pipelines using SQL, Python/Scala, and orchestration tools (e.g., Airflow, MWAA)
Ensure data quality and governance: Implement validation frameworks, manage access controls, and handle PII data responsibly
Work with complex data: Transform and optimize structured and semi-structured data (JSON, Avro, Parquet) and address schema evolution challenges
Expand capabilities with graph: Apply graph database concepts (e.g., Neo4j) for lineage, metadata, or relationship-driven use cases
Collaborate cross-functionally: Partner with analytics, product, and data science teams to translate requirements into robust and accessible datasets
Establish standards and practices for data modelling, governance, and quality to build trust and enable confident operations for AI features and business analysis
Contribute to modernization and scalability by transforming legacy data systems into a robust, future-ready platform

Skills

Key technologies and capabilities for this role

Dimensional ModelingER ModelingMedallion ArchitectureData ModelingData GovernanceData QualityBIAnalyticsReporting

Questions & Answers

Common questions about this position

Is this Data Engineer position remote?

Yes, the position is fully remote.

What technical skills are required for the Data Engineer role?

Required skills include building BI-oriented dimensional models (star/snowflake) and ER data models, developing ETL/ELT pipelines using SQL, Python/Scala, and orchestration tools like Airflow or MWAA, working with structured/semi-structured data formats like JSON, Avro, Parquet, and applying graph database concepts like Neo4j.

What is the salary or compensation for this position?

This information is not specified in the job description.

What is the company culture like at Top Hat?

Top Hat emphasizes a collaborative environment where the Data team plays a pivotal role in building AI-first personalized learning experiences, establishing standards for confident operations across teams, and modernizing legacy systems into a scalable platform.

What makes a strong candidate for this Data Engineer role?

Strong candidates have data engineering experience with expertise in data modeling, ETL/ELT pipelines, data quality/governance, handling complex data formats, graph databases, and cross-functional collaboration skills.

Top Hat

Provides educational tools and resources

About Top Hat

Top Hat provides educational tools and resources aimed at enhancing the learning experience for both educators and students. Its main products include Top Hat Pages, which allows educators to personalize content easily, and interactive response tools that engage students during lessons. Additionally, Top Hat offers a collection of fully editable textbooks, giving educators the flexibility to tailor their teaching materials. Unlike many competitors, Top Hat focuses on creating a user-friendly platform that caters to diverse learning needs across entire campuses, making it suitable for both individual courses and whole institutions. The goal of Top Hat is to empower educators to deliver personalized and equitable learning experiences, ensuring that education is accessible and engaging for all students.

Toronto, CanadaHeadquarters

2009Year Founded

$228.5MTotal Funding

SERIES_ECompany Stage

Consumer Software, EducationIndustries

201-500Employees

Risks

Increased competition may erode Top Hat's market share in EdTech.

Recent layoffs could affect employee morale and service quality.

CEO transition might lead to strategic shifts misaligned with market trends.

Differentiation

Top Hat transforms passive lectures into active learning with interactive tools.

The platform offers customizable, editable textbooks for personalized learning experiences.

Top Hat supports hybrid learning models, catering to both in-person and online environments.

Upsides

AI adoption in education enhances Top Hat's personalized learning capabilities.

Hybrid learning models expand Top Hat's market reach in higher education.

Data-driven decision-making trends increase demand for Top Hat's analytics tools.

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