Role: Senior Data Engineer
Location: Mississauga ON
Contract
Mandatory Skills: Data Lake Storage Azure Data Factory RDD/DataFrame/SQL
- Design develop optimize and maintain scalable data pipelines using Databricks (Spark/Scala) on Azure.
- Collaborate with cross-functional teams to deliver robust end-to-end data solutions.
- Write efficient SQL queries for ETL processes data validation and reporting.
- Optimize performance of complex data processing workflows.
- Implement best practices for code quality testing deployment and documentation.
- Participate in code reviews and mentor junior engineers.
- Work closely with stakeholders to understand business requirements and translate them into technical solutions.
- Integrate data solutions with other applications; exposure APIs or React-based UIs is a plus.
- Required Skills & Qualifications:
- Bachelors or Masters degree in Computer Science or related field.
- 6 years of hands-on experience in software engineering/data engineering roles.
- Strong experience with Databricks platform for big data analytics.
- Proficient in Scala programming language; solid understanding of Spark framework (RDD/DataFrame/SQL).
- Hands-on experience working on Azure cloud services (e.g. Data Lake Storage Azure Data Factory).
- Strong background in Database design & development; excellent SQL skills (T-SQL/PLSQL etc.).
- Understanding of CI/CD pipelines for automated deployments on cloud platforms.
- Experience working within Agile/Scrum methodologies.
- Advanced knowledge of Python for scripting automation and AI/ML development.
- Familiarity with Langchain for integrating and orchestrating large language model workflows.
- Hands-on experience with Azure OpenAI to leverage generative AI capabilities in applications
- Understanding of Vector Databases for efficient storage and retrieval of high-dimensional data embeddings essential for semantic search and recommendation systems.
- Knowledge of RAG (Retrieval-Augmented Generation) techniques to combine information retrieval with generative AI models for enhanced application intelligence.
Role: Senior Data Engineer Location: Mississauga ON Contract Mandatory Skills: Data Lake Storage Azure Data Factory RDD/DataFrame/SQL Design develop optimize and maintain scalable data pipelines using Databricks (Spark/Scala) on Azure. Collaborate with cross-functional teams to deliver robus...
Role: Senior Data Engineer
Location: Mississauga ON
Contract
Mandatory Skills: Data Lake Storage Azure Data Factory RDD/DataFrame/SQL
- Design develop optimize and maintain scalable data pipelines using Databricks (Spark/Scala) on Azure.
- Collaborate with cross-functional teams to deliver robust end-to-end data solutions.
- Write efficient SQL queries for ETL processes data validation and reporting.
- Optimize performance of complex data processing workflows.
- Implement best practices for code quality testing deployment and documentation.
- Participate in code reviews and mentor junior engineers.
- Work closely with stakeholders to understand business requirements and translate them into technical solutions.
- Integrate data solutions with other applications; exposure APIs or React-based UIs is a plus.
- Required Skills & Qualifications:
- Bachelors or Masters degree in Computer Science or related field.
- 6 years of hands-on experience in software engineering/data engineering roles.
- Strong experience with Databricks platform for big data analytics.
- Proficient in Scala programming language; solid understanding of Spark framework (RDD/DataFrame/SQL).
- Hands-on experience working on Azure cloud services (e.g. Data Lake Storage Azure Data Factory).
- Strong background in Database design & development; excellent SQL skills (T-SQL/PLSQL etc.).
- Understanding of CI/CD pipelines for automated deployments on cloud platforms.
- Experience working within Agile/Scrum methodologies.
- Advanced knowledge of Python for scripting automation and AI/ML development.
- Familiarity with Langchain for integrating and orchestrating large language model workflows.
- Hands-on experience with Azure OpenAI to leverage generative AI capabilities in applications
- Understanding of Vector Databases for efficient storage and retrieval of high-dimensional data embeddings essential for semantic search and recommendation systems.
- Knowledge of RAG (Retrieval-Augmented Generation) techniques to combine information retrieval with generative AI models for enhanced application intelligence.
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