Sr Data Engineer
- Toronto, ON, Canada
$110-120k · Full-time
Applications open in a new tab.
Job details
- Pay
- $110-120k
- Job type
- Full-time
- Apply by
- Posting language
- English
- Posted
Original job description
Sr Data Engineer
Toronto (hybird)
$110-120k
Global software consultancy
As a Senior Data Engineer, you will be responsible or designing and developing data processing and data persistence software components for solutions which handle data at scale. Working in agile teams, Senior Data Engineers provide strong development leadership and take responsibility for significant technical components of data systems. You will work within a multi-skilled agile team to design and develop large-scale data processing software to meet user needs in demanding production environments.
Your responsibilities will include working to develop data processing software primarily for deployment in Big Data technologies. The role encompasses the full software lifecycle including design, code, test and defect resolution. Working with Architects and Lead Engineers to ensure the software supports non-functional needs. Collaborating with colleagues to resolve implementation challenges and ensure code quality and maintainability remains high. Leads by example in code quality. Working with operations teams to ensure operational readiness. Advising customers and managers on the estimated effort and technical implications of user stories and user journeys. Coaching and mentoring team members
MINIMUM (ESSENTIAL) REQUIREMENTS:
- Strong software development experience in one of Java, Scala, or Python
- Software development experience with data-processing platforms from vendors such as AWS, Azure, GCP, Databricks.
- Experience of developing substantial components for large-scale data processing solutions and deploying into a production environment
- Proficient in SQL and SQL extensions for analytical queries
- Solid understanding of ETL/ELT data processing pipelines and design patterns
- Aware of key features and pitfalls of distributed data processing frameworks, data stores and data serialisation formats
- Able to write quality, testable code and has experience of automated testing
- Experience with Continuous Integration and Continuous Deployment techniques
DESIRABLE:
- Experience of data pipeline development
- Experience of Docker and Kubernetes
- Experience of performance tuning
- Experience of data visualisation and complex data transformations
- Experience with steaming and event-processing architectures including technologies such as Kafka and change-data-capture (CDC) products
- Expertise in continuous improvement and sharing input on data best practice
More about this job
Responsibilities
Design, develop, test, and maintain large-scale data processing and persistence components, primarily for big data platforms and production environments. Provide technical leadership, collaborate with architects and operations teams, advise on implementation effort, and coach and mentor team members.
Requirements
Candidates need strong software development experience in Java, Scala, or Python, along with experience building and deploying large-scale data processing solutions on cloud or data platforms. They should be proficient in analytical SQL, ETL/ELT design, distributed data technologies, automated testing, and CI/CD.
Skills
- Java
- Scala
- Python
- SQL
- Data Processing
- ETL/ELT
- Distributed Data Processing
- AWS
- Azure
- Google Cloud Platform
- Databricks
- Automated Testing
- Continuous Integration
- Continuous Deployment
- Docker
- Kubernetes
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Data & Analytics
- Software
- Consulting
Keywords
- Java
- Scala
- Python
- SQL
- Analytical Queries
- ETL/ELT
- Data Processing
- Data Persistence
- Big Data
- Distributed Data Processing
- Data Stores
- Data Serialization
- AWS
- Azure
- Google Cloud Platform
- Databricks
- Automated Testing
- Continuous Integration
- Continuous Deployment
- Docker
- Kubernetes
- Performance Tuning
- Data Visualization
- Complex Data Transformations
- Kafka
- Change Data Capture
- Agile
- Production Deployment
- Code Quality
- Data Pipelines