Publié il y a 3 mois
Data Office Developer (SQL , Python, Data Engineering , Data Warehousing)
@ Astra North Infoteck Inc.
Toronto, Ontario
En bref
Astra North Infoteck Inc. is hiring a Data Office Developer to build and maintain database objects, SQL queries and Python data-processing logic. The work covers ETL, data validation, reconciliation and reporting across multiple platforms, with strong SQL and Python skills required.
Responsabilités :
- Design and maintain database objects, queries and data processing logic in SQL and Python
- Support ETL, validation, reconciliation and reporting across data platforms
- Perform data quality checks and root cause analysis for defects
- Prepare data mapping documents and technical documentation
Résumé des exigences :
- Strong hands-on SQL, including complex query writing and optimization
- Proficiency in Python for data processing and automation
- Solid understanding of database concepts and data integrity
- Experience with large datasets and data quality techniques
Outils et compétences
Source et dates
Type de source non vérifié · zoho
- Date publiée par l’employeur
- 2026-07-27
- Première détection par notre source
- 2026-10-11
- Mise à jour du dossier source
- 2026-10-11
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Domaine | TI |
| Déplacements | avion : aucun · route : aucun |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Astra North Infoteck Inc.
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 426 |
Job Title: Data Office Developer (SQL, Python, ETL, Data Warehousing)
Role: Data Office Developer
Key Responsibilities
• Design, develop, and maintain database objects, scripts, queries, and data processing logic using SQL and Python
• Analyze business and technical requirements and translate them into scalable data solutions
• Support data extraction, transformation, loading, validation, reconciliation, and reporting activities across multiple data platforms
• Develop and optimize SQL queries, stored procedures, and scripts to support data analysis, reporting, and operational needs
• Work with relational and cloud-based databases such as Oracle, IQ, BigQuery, and HANA, as applicable
• Collaborate with business analysts, data analysts, architects, quality engineering teams, and business stakeholders to understand data requirements and resolve issues
• Assist in data modeling activities, including understanding source-to-target mapping, relationships, business rules, and data lineage
• Support dashboard/reporting development or validation using tools such as Tableau and Looker
• Perform data quality checks, troubleshoot data issues, and support root cause analysis for defects or production incidents
• Prepare and maintain technical documentation, data mapping documents, design notes, deployment steps, and support handover materials
Must Have Skills
• Strong hands-on experience with SQL, including writing, debugging, and optimizing complex queries
• Proficiency in Python for data processing, automation, scripting, and analysis
• Solid understanding of database concepts, including tables, views, joins, indexes, keys, normalization, stored procedures, and data integrity
• Ability to analyze data, troubleshoot issues, and validate results across source and target systems
• Experience working with large datasets and applying data quality, reconciliation, and validation techniques
• Strong communication skills with the ability to work with technical and business stakeholders
Good to Have Skills
• Experience with database platforms such as Oracle, IQ, BigQuery, and SAP HANA
• Understanding of ETL concepts, including extraction, transformation, loading, scheduling, monitoring, and error handling
• Knowledge of data modeling concepts such as conceptual, logical, and physical models, star schema, snowflake schema, facts, dimensions, and source-to-target mapping
• Experience with reporting and visualization platforms such as Tableau and Looker
• Exposure to data warehousing, analytics platforms, cloud data services, and enterprise reporting environments
Journal
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