Data Engineer

SOVRA

. Collaborate with cross-functional teams to gather data requirements.

Posted 9/18/2026full-timeRemote • CanadaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines, implementing ETL processes, and ensuring data quality and integrity across storage systems. Proficient in Python, SQL, and AWS data services, with a strong understanding of data modeling and lakehouse architecture.

Highest-signal resume keywords

Data EngineeringETL ProcessesPython ProgrammingAWS Data ServicesDbt for Data Transformation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data WarehousingData ModelingSQLPythonETL ProcessesData Quality ControlData Pipeline OptimizationInfrastructure as CodeNoSQL DatabasesAI and Machine Learning Concepts

Soft Skills

Problem-SolvingAnalytical SkillsCommunication SkillsInterpersonal SkillsDetail-Oriented

Tools & Technologies

AWS S3AWS GlueAWS AthenaDbtTerraform

Industry Keywords

Data Lakehouse PatternsMedallion ArchitectureData IntegrationData GovernanceMetadata Management

Tech Stack

Tools & technologies

AWSETLNoSQLPythonSQLTerraform

About the role

Key responsibilities & impact

Collaborate with cross-functional teams to gather data requirements.
Design, develop, and maintain scalable data pipelines integrating data from product databases and SaaS platforms.
Build ingestion pipelines into Bronze, cleansing and conforming logic in Silver, and governed Gold-layer models in dbt.
Optimize pipelines for performance, cost efficiency, and data quality.
Design and implement data models and schemas for business requirements, warehousing, and reporting.
Ensure consistency and integrity across data storage systems.
Develop and maintain ETL processes.
Monitor pipeline SLAs and data integration processes; troubleshoot production issues and incidents.
Collaborate with data source owners to ensure data availability and quality.
Implement data-quality controls and validation processes.
Partner with product, GTM, AI stakeholders, analysts, and external customers to enable data products, direct access, embedded BI, and curated exports.
Maintain catalog and lineage metadata.
Provide technical support and expertise in data engineering tools and technologies.
Contribute to API-based SaaS connectors, AI-consumable dataset design, and lakehouse cost/performance tuning.
Continuously improve data engineering practices and stay current with industry trends.

Requirements

What you’ll need

Bachelor's degree in computer science, Engineering, or a related field.
Three 3-10+ in data engineering, data warehousing, and ETL processes.
Proficiency in Python and SQL.
Experience with AWS data services, particularly S3, Glue, and Athena.
Hands-on experience with dbt for data transformation and modeling.
Knowledge of data lakehouse patterns and medallion architecture (Bronze/Silver/Gold layers).
Experience with Infrastructure as Code tools, specifically Terraform.
Experience with relational and NoSQL databases.
Understanding of AI and machine learning concepts, with the ability to prepare and structure data for AI-driven products.
Fluent in English and French, verbally and in writing.
Authorized to work in Canada; work visa or transfer sponsorship is unavailable.
Strong problem-solving, analytical, communication, interpersonal, and customer-satisfaction skills.
Detail-oriented.
Ability to work independently and as part of a team in a fast-paced environment.

Benefits

Comp & perks

Equal opportunity employer
Inclusive and equitable workplace
Pay equity commitment and regular compensation-practice reviews
Remote work arrangement