Job description

Blanc Labs is a premier partner for global enterprises, leading the way in digitization, automation, and the development of next-generation digital products and services. Our expertise in digital transformation powers businesses to accelerate service delivery, drive customer engagement, and foster growth. We are seeking a skilled Data Engineer with expertise in modern data platforms and real-time data integration to design, build, and maintain scalable data pipelines that power enterprise analytics and business intelligence. This role is ideal for someone who enjoys solving complex data engineering challenges and thrives working with distributed data processing frameworks. What You'll be Doing: Design, build, and maintain scalable data pipelines using Azure Databricks and Apache Spark Develop and optimize ETL/ELT processes to ingest, transform, and load data from diverse source systems using Azure Data Factory and Azure Databricks Implement Change Data Capture (CDC) solutions to enable real-time and near-real-time data synchronization, leveraging tools such as Azure SQL CDC , Debezium, or Databricks native CDC (Delta Live Tables) Write clean, efficient, and maintainable code in Python for data processing and automation Collaborate with data architects and analysts to translate business requirements into robust data pipeline designs on Azure Synapse Analytics / Azure Databricks Monitor, troubleshoot, and optimize data pipeline performance, reliability, and cost efficiency using Azure Monitor and Databricks observability tools Ensure data quality, consistency, and integrity across ingestion, transformation, and storage layers, including Azure Data Lake Storage (ADLS Gen2) and Delta Lake Support integration of structured and unstructured data sources into unified data platforms built on Microsoft Fabric / Azure Synapse Participate in code reviews and promote data engineering best practices across the team Document data pipelines, transformations, and architecture for team visibility and maintainability Collaborate with cross-functional teams to support analytics, reporting (Power BI), and downstream AI/ML use cases What You'll Need to Be Successful: 3+ years of experience in data engineering or a related field Strong hands-on experience with Azure Databricks for data processing and analytics workloads Proficiency with Apache Spark for large-scale distributed data processing Experience implementing CDC solutions and tools (e.g., Debezium, Azure SQL CDC, or Delta Live Tables) Strong programming skills in Python for data engineering tasks Solid understanding of SQL and relational database concepts, particularly within Azure SQL Database / SQL Managed Instance Experience building and maintaining ETL/ELT pipelines in production environments using Azure Data Factory and/or Databricks Workflows Understanding of data modeling principles and data warehousing concepts, including Azure Synapse Analytics dimensional/lakehouse modeling Strong analytical and problem-solving skills Good communication skills, with the ability to work across technical and business teams Blanc Labs is enabling a digital future. Headquartered in Toronto, we partner with clients in North & South America to digitize and automate their operations and build their next generation of digital products and services. We empower clients to enhance their digital offerings and bring creative solutions to the market faster. Learn more at www.blanclabs.com . Blanc Labs is an equal opportunity employer and is committed to providing employment in accordance with the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act. Accommodations within reason due to a disability or medical need are available on request for candidates taking part in the recruitment process.

Requirements

Must-haves

Design, build, and maintain scalable data pipelines using Azure Databricks and Apache Spark
Develop and optimize ETL/ELT processes to ingest, transform, and load data from diverse source systems using Azure Data Factory and Azure Databricks
Implement Change Data Capture (CDC) solutions to enable real-time and near-real-time data synchronization, leveraging tools such as Azure SQL CDC , Debezium, or Databricks native CDC (Delta Live Tables)
Write clean, efficient, and maintainable code in Python for data processing and automation
Collaborate with data architects and analysts to translate business requirements into robust data pipeline designs on Azure Synapse Analytics / Azure Databricks
Monitor, troubleshoot, and optimize data pipeline performance, reliability, and cost efficiency using Azure Monitor and Databricks observability tools
Ensure data quality, consistency, and integrity across ingestion, transformation, and storage layers, including Azure Data Lake Storage (ADLS Gen2) and Delta Lake
Support integration of structured and unstructured data sources into unified data platforms built on Microsoft Fabric / Azure Synapse
Participate in code reviews and promote data engineering best practices across the team
Document data pipelines, transformations, and architecture for team visibility and maintainability
Collaborate with cross-functional teams to support analytics, reporting (Power BI), and downstream AI/ML use cases
3+ years of experience in data engineering or a related field
Strong hands-on experience with Azure Databricks for data processing and analytics workloads
Proficiency with Apache Spark for large-scale distributed data processing
Experience implementing CDC solutions and tools (e.g., Debezium, Azure SQL CDC, or Delta Live Tables)
Strong programming skills in Python for data engineering tasks
Solid understanding of SQL and relational database concepts, particularly within Azure SQL Database / SQL Managed Instance
Experience building and maintaining ETL/ELT pipelines in production environments using Azure Data Factory and/or Databricks Workflows
Understanding of data modeling principles and data warehousing concepts, including Azure Synapse Analytics dimensional/lakehouse modeling
Strong analytical and problem-solving skills
Good communication skills, with the ability to work across technical and business teams

Nice-to-haves

None flagged.

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