6–8 years
Lead the design and development of end-to-end data pipelines using cloud-native and modern data engineering tools.
Architect scalable data ingestion, transformation, and storage solutions across structured and unstructured data sources.
Drive implementation of ETL/ELT frameworks, data orchestration, and workflow automation.
Collaborate with data architects, product owners, SMEs, and cross-functional teams to gather requirements and define data solutions.
Build and govern data models, metadata standards, and data quality frameworks.
Optimize data pipelines for reliability, performance, and cost efficiency.
Lead the adoption of cloud platforms such as AWS, Azure, or GCP, including services like S3, Glue, Redshift, EMR, Databricks, or Snowflake.
Oversee code reviews, best practices, and engineering standards within the team.
Ensure data security, compliance, and governance alignment (PII, encryption, audit controls).
Mentor junior data engineers and drive continuous improvement initiatives across the team.
8–12 years of experience in data engineering, with at least 3 years leading teams or technical initiatives.
Strong hands-on experience with distributed data processing frameworks (Spark, PySpark, EMR, Databricks).
Proficiency in building scalable pipelines using ETL/ELT tools and orchestration platforms (Airflow, Glue, DBT, Step Functions).
Strong SQL and programming skills (Python, Scala, or Java).
Experience with cloud data platforms: AWS (preferred), Azure, or GCP.
Knowledge of relational, NoSQL, and analytical databases (Redshift, Snowflake, BigQuery, DynamoDB, etc.).
Familiarity with CI/CD pipelines, version control (Git/GitHub), and DevOps practices for data engineering.
Strong understanding of data modeling concepts (3NF, Star/Snowflake schema).
Excellent communication skills and experience working in onshore/offshore delivery models.
Digital: Snowflake
Digital: Google Data Engineering
Digital: PySpark
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+Réjoignez KEYRUS et fañonner l'avenir de la data avec nous · +Comprendre les besoins techniques des clients afin de concevoir des solutions data performantes et évolutives · Concevoir, développer et optimiser des pipelines de données et architectures lakehouse (Databricks, Fabri ...
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· ...
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Lead Data Engineer - Toronto - Astra North Infoteck Inc.
Description
Experience Required
Role Description / Key Responsibilities
Required Qualifications
Skills
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