Publié il y a 3 jours
Data Engineer
@ Spait Infotech
Canada
SIGNAUX
En bref
Spait Infotech is hiring a full-time Data Engineer to design, build and maintain scalable data pipelines, ETL/ELT processes, data warehouses and data lakes. The work centres on SQL and Python, large datasets, data quality, validation and governance.
Responsabilités :
- Design and maintain scalable data pipelines
- Build ETL/ELT processes for data extraction and loading
- Develop and optimize SQL queries
- Maintain data warehouses and data lakes
- Ensure data accuracy, quality and governance
Résumé des exigences :
- Strong knowledge of Python and SQL
- Experience with MySQL, PostgreSQL, SQL Server or Oracle
- Understanding of ETL, ELT and data modeling
- Familiarity with Apache Spark, PySpark and Airflow
- Familiarity with AWS, Azure or Google Cloud
Outils et compétences
Source et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- 2026-11-10
- Première détection par notre source
- 2026-11-14
- Mise à jour du dossier source
- 2026-11-14
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Domaine | Données et analytique |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Spait Infotech
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 14 |
Description
Key Responsibilities
- Design, develop, and maintain scalable data pipelines.
- Build and manage ETL/ELT processes for data extraction, transformation, and loading.
- Collect, process, and transform structured and unstructured data from multiple sources.
- Develop and optimize SQL queries for efficient data processing.
- Design, implement, and maintain data warehouses and data lakes.
- Work with large datasets to ensure data accuracy, quality, and consistency.
- Develop automated workflows for data integration and processing.
- Monitor data pipelines and troubleshoot performance issues.
- Collaborate with data analysts, data scientists, and software development teams.
- Implement data validation, security, and governance practices.
- Maintain technical documentation and follow data engineering best practices.
Required Technical Skills
- Strong knowledge of Python and SQL.
- Understanding of ETL and ELT processes.
- Experience with databases such as MySQL, PostgreSQL, SQL Server, or Oracle.
- Knowledge of data warehousing concepts and data modeling.
- Familiarity with Apache Spark and PySpark.
- Understanding of Apache Airflow and workflow orchestration.
- Knowledge of data integration and pipeline development.
- Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
- Understanding of Git and version control systems.
- Knowledge of Linux and basic shell scripting.
Required Soft Skills
- Strong analytical and problem-solving abilities.
- Good communication and collaboration skills.
- Attention to detail and data accuracy.
- Ability to manage multiple tasks and meet deadlines.
- Willingness to learn new tools and technologies.
Preferred Qualifications
- Experience working with big data technologies.
- Knowledge of Snowflake, Databricks, or Amazon Redshift.
- Familiarity with Apache Kafka and real-time data processing.
- Understanding of CI/CD and DevOps practices.
- Knowledge of Agile and Scrum methodologies.
- Experience developing and deploying cloud-based data pipelines.
Journal
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