Azure Data Engineer - Mongo DB, SQL, NOSQL, Azure Data Factory, ADLS, DevOps, Oracle

Role Descriptions:

• Designing and developing data pipelines using Cloud Technologies based on business requirements and technical design.
• Collaborating with Stakeholders, Business Analysts and Data Architects to assist and translate business requirements to technical solutions
• Develop big data and analytic solutions leveraging new or existing technology
• Exploratory data analysis by querying and processing data stores and databases and generate reports.
• Design, upgrade and implement new data workflows.
• Write and maintain technical documentation
• Executes updates, patches, and other activities required to maintain and enhance the operations of on-premise or cloud-based environments

Must-Have:

• Experience working as Data Engineer with focus on data ingestion, transformation, curation and with good understanding of Mongo DB
• Experienced in programming/scripting languages such as Pyspark
• Experienced with working on Structured and Semi-Structured datasets.
• Experience working with Microsoft Azure Data Platform, specifically Azure SQL Database, Azure Data Factory, ADLS storage account, Azure DataBricks and DevOps
• Experienced in creating data pipelines & developing complex and optimized queries
• Experience with implementing CI / CD pipeline on GitHub, Jenkins / JGP.
• Experience writing complex SQL and NoSQL jobs to analyze data in traditional DBMS (MS-SQL, Oracle) environments
• Experience with integrating to back-end/legacy environments
• Experience integrating business and technology teams
• Excellent organizational and time management skills, strong business presence with ability to multi-task and effectively deal with competing priorities

Good-to-Have:

Previous work experience in the financial sector (insurance or benefits industry).

Pay:

$65.00-$70.00 per hour

Work Location:

Hybrid remote in Toronto, ON (Toronto District)