Support the architecture and development of cloud-based systems to manage and improve the interface between Semios data and its consumers.
Assist in developing and maintaining infrastructure to process and store data, integrate data-driven models, and automate manual processes.
Contribute to the implementation of scalable data processing and analytics solutions in a cloud environment.
Help build reliable, monitorable, and fault-tolerant data pipelines and data processes.
Develop data tools and utilities that help analytics and data science team members work more efficiently.
Work with senior team members to assemble and clean large data sets that meet business requirements.
Participate in performance tuning, query optimization, and refactoring under guidance from more experienced engineers.
Write and maintain clear documentation of processes and products.

Requirements

Good foundational SQL skills and the ability to write clean, understandable queries
Programming experience in Python, NodeJS, or another imperative language
A willingness to learn, collaborate, and contribute in both autonomous and team settings
Exposure to at least one Data Warehouse technology (e.g., BigQuery, Redshift, Snowflake, Oracle, On-Prem) through coursework, internships, or project experience
Strong verbal and written communication skills, with the ability to break down technical concepts for different audiences
Some familiarity with working with large data sets and an interest in developing deeper Big Data expertise
Introductory experience or coursework related to cloud platforms (AWS, GCP, or similar)
Interest in learning orchestration tools (e.g., like Prefect, Airflow, Dagster, Kubeflow, etc.) and version control (Git)
Strong troubleshooting and problem-solving abilities, with a drive to learn how to identify and resolve issues effectively
Nice to have: Experience with relational databases such as Postgres or MySQL
Exposure to containerization technologies (Docker, Kubernetes)
Interest or coursework in IoT Cloud and IoT data
Familiarity with dbt and dlt
Academic background or certifications related to Big Data, cloud computing, or data engineering

Benefits

Purposeful Work: Make a global impact by advancing sustainable food production.
Our People: Work with a fun, collaborative, and supportive team.
Recharge: Generous vacation policy, company-paid holidays and year-end winter break.
Work Flexibility: Hybrid working arrangements and strong work-life balance culture.
Office location that is convenient via transit and bike paths
Extended medical plan, Health Spending Account and Personal Spending Account, with premiums paid by the company
Group RRSP, which includes a 3% company paid match after one year of employment

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

SQLPythonNodeJSBigQueryRedshiftSnowflakeOracleAWSGCPDocker

collaborationcommunicationtroubleshootingproblem-solvingwillingness to learnautonomous workteamworkdocumentation

Big Datacloud computingdata engineering