RQ11099 - Sr. DataOps/Cloud Data Engineer
- Toronto, ON, Canada
$68.28 to $102.42 CAD / hour
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Job details
- Pay
- $68.28 to $102.42 CAD / hour
- Posting language
- English
Original job description
RQ11099 - Sr. DataOps/Cloud Data Engineer
1-year 11-month contract (457 business days) - possible extension
ONSITE 5 days - 5700 Yonge St. Toronto'
Security Level: CRJMC
MUST HAVES:
· Data engineering (pandas, pyspark)
· Data lakehouse solutions such as Databricks (Delta Lake).
· Working with XLSX, CSV, JSON files, relational databases, cloud storage, structured and unstructured data
· Experience using AWS Services such as Glue, StepFunctions, Lambda, S3
· Extract/Transform/Load data using tools such as Informatica IDMC
Responsibilities:
Design, develop, test, implement, and troubleshoot:
· data pipelines using various tools such as Databricks, Azure Data Factory, AWS Glue
· complex data transformation procedures
· data models for data warehouses and lakehouses
AI Disclaimer: Source Code may use artificial intelligence (AI) tools to assist in certain aspects of its recruiting and business operations.
Note: The higher end of the range is intended for absolutely exceptional candidates who meet all must-have requirements and most or all nice-to-have qualifications. The client will evaluate candidates based on both rate expectations and overall skill set when shortlisting.
INCORPORATED RATE RANGE (7.25 billable hours per day)
- $85.35/hr - $102.42/hr Inc.
T4 RATE RANGE (7.25 billable hours per day)
- $68.28/hr - $81.94/hr T4
More about this job
Responsibilities
The Senior DataOps/Cloud Data Engineer at Source Code will design, build, test and fix data pipelines that move and transform data. The role also covers building data models for warehouses and lakehouses.
Requirements
Candidates need hands-on data engineering with pandas and PySpark, lakehouse experience such as Databricks with Delta Lake, and AWS skills with Glue, Step Functions, Lambda and S3. They also need experience with Informatica IDMC for ETL and working with XLSX, CSV, JSON, relational databases and cloud storage.
Skills
- Databricks
- Delta Lake
- PySpark
- pandas
- AWS Glue
- AWS Step Functions
- AWS Lambda
- AWS S3
- Informatica IDMC
- Azure Data Factory
- Python
- SQL
- ETL
- ELT
- Data pipeline development
- Data transformation
- Data modeling
- Data warehousing
- Data lakehouse architecture
- Relational databases
- Structured and unstructured data
- XLSX
- CSV
- JSON
- Troubleshooting
Categories
- Data & Analytics
- Software
- Technology
Keywords
- Data engineer
- DataOps
- Cloud data engineer
- Databricks
- Delta Lake
- Lakehouse
- PySpark
- pandas
- AWS Glue
- AWS Step Functions
- AWS Lambda
- AWS S3
- Informatica IDMC
- Azure Data Factory
- ETL
- ELT
- Data pipelines
- Data warehouse
- Data modeling
- Contract
Tools
- Databricks
- Delta Lake
- PySpark
- pandas
- AWS Glue
- AWS Step Functions
- AWS Lambda
- AWS S3
- Informatica IDMC
- Azure Data Factory
Languages
- English
Seniority
Senior