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Senior Data Engineer with experience building data scripts using ETL software

Job Type: Contract
Positions to fill: 1
Start Date: Jan 31, 2023
Job End Date: Feb 01, 2024
Pay Rate: Hourly: Negotiable
Job ID: 126649
Location: Calgary, Edmonton, Halifax, London, Montreal, Ottawa, Regina, Toronto
Our client is seeking a Senior Data Engineer with experience building data scripts using ETL software 

Duration is 1 year, work is 100% remote

The Data Engineer Data & Analytics will build data scripts using ETL software to enable advanced analytics and data science across the company and the stakeholders. Consultant will construct and support Data Ingestion & ETL pipelines, building microservices and participate in exploratory data analysis. They will need to conduct development testing and participate in all testing and deployment phases.  

Must Haves
  • Experience with Big Data technologies (e.g Azure Data Lake, Storage, Snowflake)
  • Strong Experience with SQL, Pyhon, Scala
  • Experience with ETL technologies (Talend, Databricks, Azure Data Factory)
  • Proficiency with relational databases (Oracle, DB2, SQL Server, etc.) and SQL
  • Experience with cloud computing platforms (Microsoft Azure, AWS, Google Cloud or Snowflake) and with Data warehousing
  • Experience working in an Agile team environment
  • Knowledge of the tooling for deployment, monitoring and site reliability
  • Excellent communication and problem-solving skills
  • Design and develop processing pipelines that ingest data into a data lake
  • Design and develop ETL pipelines using multiple sources of data in various formats between data lake and data warehouse.
  • Conduct metadata management, data cleansing and conforming.
  • Use sound agile development practices (code reviews, testing, etc) to develop and deliver data pipelines
  • Provide day-to-day support and technical expertise to both technical and non-technical teams
  • Exhibit sound judgement, keen eye for details and tenacity for solving difficult problems.
  • Use strong analytical skills and support use of data for sound decision making.
  • Help build data engineering expertise and framework
  • Develop expertise around the data and it flows
  • Collaborate with programmers, data analyst, and organizational leaders to identify opportunities for process improvements Translate business needs into technical requirements