About the roleAs an
Azure Data Engineer (Data Lake and Streaming), you will make an impact by designing and delivering scalable, high-performance data platforms powered by Data Lake and streaming architectures. You will be a valued member of the data engineering team and collaborate closely with architects, product owners, and cross-functional engineering teams to deliver data-driven solutions that support strategic business decisions.
In this role, you will:- Design and build scalable Data Lake solutions supporting structured and unstructured data across business domains
- Develop and maintain batch and real-time data pipelines using Spark, Kafka, and modern data frameworks
- Implement reliable, high-throughput streaming solutions using event-driven architectures
- Develop Python-based automation and reusable components to orchestrate and optimize data workflows
- Optimize performance, scalability, and reliability across data platforms through tuning and monitoring best practices
Work modelWe believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring
4 days per week in a Cognizant office in Mississauga. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
What you need to have to be considered- Strong hands-on experience with Apache Spark (DataFrames, Spark SQL, large-scale processing)
- Proficiency in Python (must-have) and/or Scala, with a focus on automation and data engineering
- Experience building and managing Data Lake architectures on cloud platforms (Azure, AWS, or GCP)
- Hands-on expertise with Kafka and event-driven/streaming architectures
- Solid experience with ETL/ELT frameworks, large-scale data pipelines, and data platform migrations
- Familiarity with CI/CD pipelines, Git, and DevOps practices for data engineering workloads
These will help you stand out- Strong focus on Python-based automation and orchestration within data ecosystems
- Experience optimizing Spark jobs, Kafka configurations, and distributed data systems
- Exposure to data governance, cataloging, and metadata management tools
- Experience working in agile delivery environments with cross-functional teams
- Familiarity with AI-assisted development tools and ability to validate generated code
We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting ideas to this role.
We regularly assess market data to ensure we offer a competitive compensation package for our associates. The base salary for this position ranges between $90,000 - $109,000 per year. Where the successful candidate may fall within the range depends on relevant education, work and/or management experience and other business-related and job-necessary qualifications. This position is also eligible for Cognizant's discretionary annual performance-based bonus, as well as benefits that support your physical, mental and financial wellbeing.
Note: The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
Cognizant will only consider applicants for this position who are legally authorized to work in Canada without requiring employer sponsorship, now or at any time in the future.
