Description - External
Job Title – Data engineer – Spark + Scala Required
About the role
As a Spark Scala Developer , you will make an impact by designing, developing, and supporting batch data processing pipelines using Apache Spark on Google Cloud Platform (GCP) . You will be a valued member of the data engineering team and work collaboratively with cross‑functional engineering, operations, and client stakeholders .
In this role, you will:
Design, develop, and maintain batch data processing jobs using Apache Spark (Scala) on GCP
Enhance and support Spark Scala batch pipelines across development and production environments
Perform end‑to‑end development activities including coding, unit testing, and integration testing
Deploy code to production following established release and deployment processes
Monitor batch jobs, investigate failures, analyze logs, and resolve production issues
Validate and reconcile data across staging and production to ensure accuracy and reliability
We strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a remote position open to qualified applicants in Canada. Regardless of your working arrangement, we are here to support a healthy work-life balance though 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 programming experience in Scala with hands‑on expertise in Apache Spark
Experience working with Google Cloud Platform (GCP) services including Dataproc, BigQuery, Cloud Storage, and Airflow
Solid understanding of batch data processing frameworks and distributed systems
Experience performing data validation, data quality checks, and debugging production data issues
Ability to analyze logs, identify root causes, and resolve production incidents
Experience working in Unix/Linux environments and using shell scripting
These will help you stand out
Experience supporting large‑scale, production data pipelines
Proven ability to optimize Spark jobs for performance, scalability, and cost efficiency
Strong problem‑solving and analytical skills
Ownership mindset with attention to detail and quality
Experience documenting data pipelines and operational processes
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 things to this role.
Salary and Other Compensation :
Applications will be accepted until June 18, 2026.
The annual salary for this position is between CAD 81,000 - CAD 140,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- Medical/Dental/Vision/Life Insurance
- Paid holidays plus Paid Time Off
- Long-term/Short-term Disability
- Paid Parental Leave
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
