Data Office Developer : Toronto, ON (Hybrid) : FTE
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- Experience: 8+ years
- Posting language
- English
- Posted
Original job description
Role: Data Office Developer
Location: Toronto, ON (Hybrid)
Experience: 8+ years
Type: Full Time Permanent
Key Responsibilities
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Design, develop, and maintain database objects, scripts, queries, and data processing logic using SQL and Python.
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Analyze business and technical requirements and translate them into scalable data solutions.
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Support data extraction, transformation, loading, validation, reconciliation, and reporting activities across multiple data platforms.
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Develop and optimize SQL queries, stored procedures, and scripts to support data analysis, reporting, and operational needs.
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Work with relational and cloud-based databases such as Oracle, IQ, BigQuery, and HANA, as applicable.
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Collaborate with business analysts, data analysts, architects, quality engineering teams, and business stakeholders to understand data requirements and resolve issues.
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Assist in data modeling activities, including understanding source-to-target mapping, relationships, business rules, and data lineage.
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Support dashboard/reporting development or validation using tools such as Tableau and Looker.
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Perform data quality checks, troubleshoot data issues, and support root cause analysis for defects or production incidents.
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Prepare and maintain technical documentation, data mapping documents, design notes, deployment steps, and support handover materials.
Must have Skills
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Strong hands-on experience with SQL, including writing, debugging, and optimizing complex queries.
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Proficiency in Python for data processing, automation, scripting, and analysis.
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Solid understanding of database concepts, including tables, views, joins, indexes, keys, normalization, stored procedures, and data integrity.
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Ability to analyze data, troubleshoot issues, and validate results across source and target systems.
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Experience working with large datasets and applying data quality, reconciliation, and validation techniques.
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Strong communication skills with the ability to work with technical and business stakeholders.
Good to have Skills
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Experience with database platforms such as Oracle, IQ, BigQuery, and SAP HANA.
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Understanding of ETL concepts, including extraction, transformation, loading, scheduling, monitoring, and error handling.
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Knowledge of data modeling concepts such as conceptual, logical, and physical models; star schema; snowflake schema; facts; dimensions; and source-to-target mapping.
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Experience with reporting and visualization platforms such as Tableau and Looker.
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Exposure to data warehousing, analytics platforms, cloud data services, and enterprise reporting environments.
More about this job
Responsibilities
Design, develop, and optimize database objects, SQL queries, Python scripts, and data processing solutions, supporting data integration, validation, reconciliation, and reporting across platforms. Collaborate with technical and business teams to clarify requirements, troubleshoot data issues, support data modeling and reporting, and maintain technical documentation.
Requirements
Requires 8+ years of experience, strong hands-on SQL skills, proficiency in Python, and a solid understanding of database concepts. Candidates should be able to analyze and validate large datasets, troubleshoot data issues, and communicate effectively with technical and business stakeholders; experience with ETL, data modeling, Oracle, IQ, BigQuery, SAP HANA, Tableau, or Looker is beneficial.
Skills
- SQL
- Python
- Database Development
- Query Optimization
- Data Processing
- ETL
- Data Validation
- Data Reconciliation
- Data Quality
- Data Modeling
- Source-to-Target Mapping
- Troubleshooting
- Tableau
- Looker
- Oracle
- BigQuery
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
Keywords
- SQL
- Python
- Oracle
- IQ
- BigQuery
- SAP HANA
- Tableau
- Looker
- ETL
- Data Processing
- Data Extraction
- Data Transformation
- Data Loading
- Data Validation
- Data Reconciliation
- Data Quality
- Data Modeling
- Source-to-Target Mapping
- Data Lineage
- Stored Procedures
- Database Optimization
- Relational Databases
- Cloud Databases
- Data Warehousing
- Analytics Platforms
- Reporting
- Star Schema
- Snowflake Schema
- Root Cause Analysis
- Technical Documentation