Data Engineer

SOVRA; Montreal (administrative region); On-site; CAD 85,000 - 120,000; Full time

Job summary

SOVRA is seeking a hands-on Data Engineer to design and maintain end-to-end data pipelines in a lakehouse environment on AWS. You will own ingestion from various sources, transform with dbt, and publish governed Gold models for internal teams and external customers.

You will partner with product, GTM, and AI stakeholders to translate use cases into data products, ensure data quality, and support analytics with reliable data access. Fluency in English and French is required.

Qualifications

• Bachelor's degree in computer science, engineering, or a related field.
• 3–10+ years in data engineering, data warehousing, and ETL processes.
• Proficiency in Python and SQL.
• Experience with AWS data services (S3, Glue, Athena).
• Hands-on experience with dbt for data transformation and modeling.
• Knowledge of data lakehouse patterns and medallion architecture (bronze/silver/gold).
• Experience with Infrastructure as Code (IaC) tools, specifically Terraform.
• Experience with relational and NoSQL databases.
• Fluent in English and French, both verbally and written.
• Authorized to work in Canada (no visa sponsorship).

Responsibilities

• Collaborate with cross-functional teams to gather data requirements.
• Design, develop, and maintain scalable data pipelines from multiple sources.
• Optimize data pipelines for performance, cost efficiency, and data quality.
• Design and implement data models and schemas to meet business requirements.
• Develop and maintain logical and physical data models to support data warehousing and reporting.
• Ensure data consistency and integrity across data storage systems.
• Design, develop, and maintain ETL processes to extract, transform, and load data.
• Monitor data integration processes, troubleshoot issues, and resolve them.
• Collaborate with data source owners to ensure data availability and quality.
• Implement data quality controls and validation processes.
• Work with data analysts and stakeholders to ensure data availability for analytics.
• Provide technical support and stay up-to-date with industry trends.

Skills

Problem solving

Analytical thinking

Communication

Detail oriented

Team collaboration

Education

Bachelor's degree in CS/Engineering

Tools

dbt

Terraform

AWS S3

AWS Glue

AWS Athena

Job description

About Sovra

SOVRA is a leading public procurement platform trusted by more than 7,000 government agencies and over 1 million suppliers across North America. Our work sits at the intersection of technology, public service, and accountability, helping governments operate more efficiently and transparently on behalf of the communities they serve.

SOVRA is a leading public procurement platform trusted by more than 7,000 government agencies and over 1 million suppliers across North America. Our work sits at the intersection of technology, public service, and accountability, helping governments operate more efficiently and transparently on behalf of the communities they serve.

THE ENVIRONMENT

SOVRA runs a lakehouse platform (Bronze / Silver / Gold layers on Apache Iceberg), with AWS DMS and Zero-ETL for ingestion, dbt for transformation, and AWS-native services (S3, Glue, Athena, Bedrock) for storage, compute, and AI enablement. The Data Engineering Specialist works inside this stack, embedded in the Data Platform team.

What we're looking for.

A hands-on data engineer fluent in SQL, Python, dbt, and modern lakehouse patterns on AWS, comfortable owning pipelines end-to-end — from source-system CDC through governed Gold models and used to working in a governed, multi-consumer environment where data is treated as a product, not a report.

Daily rhythm.

A short standup with the Data Platform team to review pipeline health, ingestion status, and delivery blockers. Working sessions with data analysts on Gold-layer model validation, and pairing with fellow data engineers on shared transformation logic.

Core engineering work (majority of the week).

Building and maintaining ingestion pipelines from source systems (product databases, and eventually SaaS platforms) into the Bronze layer; developing Silver-layer cleansing and conforming logic; and modeling Gold-layer datasets in dbt for consumption by internal teams and external customers.

Consumer enablement.

Partnering with internal product, GTM, and AI stakeholders to translate use cases into Gold-layer data products, and supporting external customer needs (direct data access, embedded BI, curated exports) through the platform's productized surfaces.

Reliability and governance.

Monitoring pipeline SLAs, resolving production incidents, maintaining catalog and lineage metadata, and running data-quality checks. Occasional bounded one-time work — regulatory data requests, audit evidence, incident investigations.

Platform evolution.

Contributing to new ingestion patterns (e.g. API-based SaaS connectors, Data streams, etc...), AI-consumable dataset design, and cost/performance tuning of the lakehouse.

Main Responsibilities

• Collaborate with cross-functional teams to gather data requirements.
• Design, develop, and maintain scalable data pipelines to process and integrate data from various sources.
• Optimize data pipelines for performance, cost efficiency, and data quality.
• Design and implement data models and schemas that meet business requirements.
• Develop and maintain logical and physical data models to support data warehousing and reporting.
• Ensure data consistency and integrity across different data storage systems.
• Design, develop, and maintain ETL processes to extract, transform, and load data from multiple sources.
• Monitor data integration processes, troubleshoot, and resolve any issues that may arise.
• Collaborate with data source owners to ensure the availability and quality of the data.
• Implement data quality controls and validation processes to ensure data accuracy and reliability.
• Collaborate with data analysts, and other stakeholders to ensure data availability and accessibility for analytical purposes.
• Provide technical support and expertise in data engineering and related tools and technologies.
• Continuously improve data engineering practices and stay up-to-date with industry trends and best practices.

Profile

• Strong problem-solving, analytical, and communication skills.
• Detail oriented
• Ability to work independently and as part of a team in a fast-paced environment;
• Good interpersonal and communication skills and focus on customer satisfaction

Qualifications

• Bachelor's degree in computer science, Engineering, or a related field.
• Three 3-10+ in data engineering, data warehousing, and ETL processes.
• Proficiency in programming languages such as Python and SQL
• Experience with AWS data services, particularly S3, Glue, and Athena
• Hands-on experience with dbt (data build tool) for data transformation and modeling
• Knowledge of data lakehouse patterns and medallion architecture (bronze/silver/gold layers)
• Experience with Infrastructure as Code (IaC) tools, specifically Terraform
• Experience with relational and NoSQL databases
• Understanding of AI and machine learning concepts, with the ability to prepare and structure data to support AI-driven products
• Fluent in English and French, both verbally and written
• Authorized to work in Canada—unfortunately we are not able to sponsor work visas or transfers at this time.

Thank you for your interest in SOVRA.

At SOVRA, we are committed to fostering an inclusive and equitable workplace. We are an equal opportunity employer and do not discriminate against any employee or applicant for employment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, marital status, veteran status, or any other characteristic protected by applicable laws. We provide a work environment free from discrimination and harassment. In addition, we are committed to ensuring pay equity across our organization and regularly review our compensation practices.