Data Engineer
- Montreal, QC, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- Experience: 6+ Years
- Posting language
- English
- Posted
Original job description
Blutic is looking for an experienced Data Engineer with 6+ years of experience and strong hands-on expertise in designing and building scalable ETL/ELT pipelines using Azure Data Factory (ADF), Azure Databricks (PySpark), and Snowflake.
This is W2 (Hybrid) opportunity.
Location: Montreal, Canada
Experience: 6+ Years
Required Qualifications:
- 6+ years in data engineering or ETL development
- Strong hands-on experience with Snowflake (Snowpipe, Streams and Tasks, performance tuning).
- Hands-on Azure Databricks and PySpark, including Delta Lake.
- Proficiency in Azure Data Factory, including parameterized and metadata-driven pipelines.
- Strong SQL and PL/SQL or T-SQL, including stored procedures.
- Experience with Informatica PowerCenter or IICS, ideally including migration to cloud platforms.
- Python for data processing, validation, and automation.
- Experience with data validation and reconciliation in financial or regulated environments.
- Familiarity with Git, Azure DevOps CI/CD, and Agile/Scrum delivery.
Key Responsibilities:
- Design and build scalable ETL/ELT pipelines using Azure Data Factory, Azure Databricks (PySpark), and Snowflake.
- Develop Medallion architecture (Bronze, Silver, Gold) on Delta Lake, using Delta Live Tables and Unity Catalog for governance.
- Build Snowflake solutions using Snowpipe, Streams, Tasks, Dynamic Tables, and Snowpark (Python).
- Create metadata-driven, parameterized, reusable pipeline frameworks to speed up source onboarding.
- Write and tune complex SQL, PL/SQL, and T-SQL, including stored procedures, functions, and packages.
- Implement CDC and incremental loading (Delta Lake MERGE, watermark logic) across batch and near real-time pipelines.
- Build data quality, reconciliation, auditing, and exception-handling frameworks to support regulatory and financial reporting.
- Optimize performance and cost across Databricks clusters, Snowflake warehouses, and ADF pipelines.
- Automate CI/CD with Azure DevOps, Git, and Terraform; support release management across environments.
- Provide production support, root cause analysis, and monitoring for critical pipelines.
- Work with architects, analysts, finance, risk, and compliance teams, and mentor junior engineers.
More about this job
Responsibilities
Design, build, and optimize scalable ETL/ELT pipelines and data platforms using Azure Data Factory, Databricks, Delta Lake, and Snowflake, including incremental loading, governance, and reusable pipeline frameworks. Establish data quality and reconciliation controls, automate CI/CD, support production operations, and collaborate with business and technical teams while mentoring junior engineers.
Requirements
Requires 6+ years of data engineering or ETL development experience, with hands-on expertise in Snowflake, Azure Databricks and PySpark, Delta Lake, and Azure Data Factory. Candidates should also have strong SQL skills, Python, experience with Informatica, data validation in regulated or financial environments, and familiarity with Git, Azure DevOps CI/CD, and Agile/Scrum.
Skills
- Azure Data Factory
- Azure Databricks
- PySpark
- Snowflake
- Delta Lake
- ETL/ELT Pipelines
- SQL
- PL/SQL
- T-SQL
- Informatica PowerCenter
- IICS
- Python
- Data Validation
- Azure DevOps
- Git
- Terraform
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- Azure Data Factory
- Azure Databricks
- PySpark
- Snowflake
- Snowpipe
- Streams And Tasks
- Dynamic Tables
- Snowpark
- Delta Lake
- Delta Live Tables
- Unity Catalog
- Medallion Architecture
- ETL/ELT
- Informatica PowerCenter
- IICS
- SQL
- PL/SQL
- T-SQL
- Python
- Change Data Capture
- Incremental Loading
- Data Quality
- Data Reconciliation
- Azure DevOps
- Git
- Terraform
- CI/CD
- Agile/Scrum
- Financial Reporting
- Regulatory Compliance