CLDRSRC9598 - DataOps/Cloud Data Engineer - Toronto- Onsite Contract

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

Skills

Experience and Skill Set Requirements

• Data engineering Experience
• Programming & scripting: Python, SQL, Linux shell, PowerShell.
• Data manipulation/analysis using pandas and pyspark.
• Working with XLSX, CSV, JSON files, relational databases, cloud storage, structured and unstructured data (40%)
• Cloud experience
  • AWS and/or Azure services.
  • Cloud data warehouse solutions such as AWS Redshift.
  • Data lakehouse solutions such as Databricks (Delta Lake).
• Data processing orchestration/automation (25%)
• Data Warehouse ETL tools (such as Azure Data Factory, AWS Glue) as well as cloud agnostic tools such as Informatica IDMC.
• Data modeling & architecture: relational and dimensional modeling.
• Data reporting/visualization (25%)

Other Skills

• Full SDLC from requirements gathering, design, implementation, testing to deployment and production support
• Project management (agile/scrum and waterfall)
• Change and Incident management
• Communication, presentation and negotiation skills
• Consulting, problem-solving and decision-making skills (5%)

Public Sector Experience

• working in OPS and/or public sector in general (5%)