Int. Data Engineer to build a data pipeline to transfer the data from the enterprise data lake for enabling AI use cases - 19364

Int. Data Engineer to build a data pipeline to transfer the data from the enterprise data lake for enabling AI use cases - 19364

Duration of Contract: 7 months (until end of 2025)

Location: Canada (Remote)

As a Data Engineer, you will be responsible for designing, building and running the data driven applications which enable innovative, customer centric digital experiences.

You will be working as part of a friendly, cross-discipline agile team who helps each other solve problems across all functions. As a custodian of customer trust, you will employ best practice in development, security, accessibility and design to achieve the highest quality of service for our customers.

Our development team uses a range of technologies to get the job done: Google Cloud Platform(GCP), PySpark, Dataflow, BigQuery, Looker Studio, Google Cloud Scheduler, Shell scripting, Pubsub, Elasticsearch, LLMs, Gemini Pro, GitHub, Terraform etc to provide a modern, easy to use data pipeline.

You will be part of the team building a data pipeline to transfer the data from our enterprise data lake for enabling our AI use cases.

You are a fast learner, highly technical, passionate data engineer looking to work within a team of multidisciplinary experts to improve your craft and contribute to the data development practice.

Must-Have Skills:

• Python on Visual Studio Code, Cline/Copilot or other AI based coding experience - 4+ years exp
• Google Cloud - Vertex AI, M/L Pipelines, Gen AI Models, BigQuery, Dataflow, Terraforms, YAML, Pyspark
• Extensive knowledge of building complex SQL queries and stored procedures
• Tableau or Looker Studio
• JIRA and Agile Methodology

Nice-to-Have Skills:

• Google Workspace, App Scripts
• JavaScript, React JS, Node JS
• Telecom Domain Knowledge

You're the missing piece of the puzzle

• A passion for data
• Interest and ability to learn new languages & technologies as needed
• Familiar with the execution sequence of ETL Flows using Google Platforms
• Experience with Spark, Beam, Airflow, Cloud SQL, BigQuery, MSSQL
• Basic understanding of data warehouse, data lake, OLAP and OLTP applications

Great-to-haves

• Intermediate level candidates with 4-6 years of relevant experience
• Experience with Big data related tools and technologies
• Experience with SQL, Unix, Shell scripting
• Experience with data visualization tools such as Tableau, Domo, Looker

Interview process:

• Round 1: Off line coding assignment on Google Cloud, BigQuery and Python followed by Video call technical interview.
• Round 2: Behavioral Questions Interviews with Leadership team