Azure Data Engineering Specialist; Databricks

Position

Description:

Location:

Toronto
- On site 3 days a week

Are you an experienced Azure Data Engineering professional interested in working in a talented and collaborative team developing Cloud, Data and AI solutions for leading global clients? Do you regularly find yourself in conversations on disparate and dispersed data sources and feel the need to create a robust data engineering infrastructure to sort that mess out? If you have that technical expertise of building pipelines and enabling data engineering or ETL in organizations, a genuine flair for solving problems, and the mindset to collaborate with diverse clients and team members alike, we're looking for you.

** Expertise in Azure Data Factory, Azure Databricks and Spark/Pyspark is required for this role*
* ** This is a hands-on role**

Your future duties and responsibilities:

As an Azure Data Engineer (Databricks) on this team your responsibilities will include:

· Delivering on areas of data preparation and transformations and ETL or ELT development on Azure - Azure Data Factory (ADF), Azure Databricks, Azure Data Lake (ADLS), Synapse, Azure SQL database, Azure SQL Datawarehouse

· Building Batch and Streaming data pipelines with Databricks

· Working in a business environment with large-scale, complex and big data datasets and dispersed data sources

· Using SQL or Advanced SQL and Python skills as necessary

· Gathering client requirements, coding and building Data Engineering pipelines in Azure

· Implementing proof of concepts to show value and then package and scale to full data engineering scale on both on-prem and cloud environments

· Strategically collaborating with the clients to explore data sources and build Power BI dashboards with Azure Data Engineering
Supporting and collaborating with the other Data Engineers or Data Scientists in the team with technical knowledge

Required qualifications to be successful in this role:

Essential skillsets and expertise needed:

· Azure Databricks, Azure Data Factory, and Spark/Pyspark experience is mandatory

· Total 5+ years' experience in Data Engineering is required to apply to this role

· Experience with building streaming pipelines on Azure

· 5 years or more in Azure Data Engineering

· Data analysis, storage, data pipelines, and orchestration

· Expert Python and SQL skills

· Experience working on Big Data
Nice to Have Qualifications

· Experience with Informatica

· Experience in data engineering with ML projects

· Experience with data pipeline and workflow management tools eg. Airflow, Jenkins etc.

· Experience working with Spark/ Hive/HDFS

· Experience in building strong Power BI Dashboards with DAX queries, Power Apps, Power Automate, and Logic Apps

CGI is providing a reasonable estimate of the pay range for this role. The determination of this range includes factors such as skill set level, geographic market, experience and training, and licenses and certifications. Compensation decisions depend on the facts and circumstances of each case. A reasonable estimate of the current range is $95,-$,. This role is an existing vacancy

#LI-AB19

Use of the term ‘engineering’ in this job posting refers to the technical sense related to Information Technology (IT) and does not imply that the individual practices engineering or possesses the requisite license as prescribed by the applicable provincial or territorial engineering regulator. We are seeking individuals with expertise in IT engineering-related functions, but licensure from an engineering regulator is not a prerequisite for this position.

Engineering is a regulated profession in Canada which is restricted in terms of use of titles and designation.

Skills: