Data Engineer

Acestack; Toronto; On-site; CAD 140,000 - 190,000; Full time

Job summary

Acestack in Toronto, ON is seeking an experienced Data Engineer with deep AWS data pipeline expertise to design scalable data lakes and warehouses for banking clients.

The role focuses on building end-to-end ETL/ELT pipelines using S3, Redshift, Glue, Lambda, and Spark, migrating from IBM Netezza, and ensuring data quality and security.

You will collaborate with stakeholders, implement CI/CD for deployments, and mentor teams on best practices in data architecture.

Qualifications

• 12+ years of experience in data engineering and data warehousing.
• Strong experience in the banking and financial services domain.
• Hands-on with Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift.
• Experience with IBM Netezza and migration to AWS environments.
• Knowledge of Kafka, Spark, and batch data processing.
• Strong understanding of data warehouse architecture and data lake solutions.

Responsibilities

• Design, develop, and maintain scalable data pipelines and workflows on AWS.
• Build and manage data lakes and data warehouses using Amazon S3 and Redshift.
• Develop ETL/ELT processes using AWS Glue, Lambda, Spark, and related technologies.
• Implement Kafka message processing, batch data ingestion, and business-layer data processing.
• Optimize data ingestion, transformation, and loading processes.
• Ensure data quality, governance, security, performance, and scalability.
• Monitor and troubleshoot data pipelines and workflows using AWS services.
• Automate deployments through CI/CD pipelines.
• Collaborate with clients, data users, and stakeholders to understand requirements.
• Develop reusable data engineering frameworks and design patterns.
• Perform data onboarding using established frameworks.
• Analyze existing IBM Netezza code and design migration solutions for AWS Data Lake.

Skills

Data warehousing

ETL/ELT development

AWS data services

Banking domain

Data pipelines design

CI/CD tooling

Tools

AWS S3

AWS Glue

AWS Lambda

Amazon Redshift

Kafka

Spark

IBM Netezza

Snowflake

Databricks

Airflow

Job description

Job Title: Data Engineer
Job Type: Full Time
Location: Toronto, ON (Onsite)

Job Description

We are seeking an experienced Data Engineer with strong data warehouse expertise and extensive experience in the banking and financial services domain. The ideal candidate will have 12+ years of experience in data engineering and hands-on expertise designing and developing scalable data pipelines, data lakes, and data warehouses on AWS.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and workflows on AWS
• Build and manage data lakes and data warehouses using Amazon S3 and Redshift
• Develop ETL/ELT processes using AWS Glue, Lambda, Spark, and related technologies
• Implement Kafka message processing, batch data ingestion, and business-layer data processing
• Optimize data ingestion, transformation, and loading processes
• Ensure data quality, governance, security, performance, and scalability
• Monitor and troubleshoot data pipelines and workflows using AWS services
• Automate deployments through CI/CD pipelines
• Collaborate with clients, data users, and stakeholders to understand requirements
• Develop reusable data engineering frameworks and design patterns
• Perform data onboarding using established frameworks
• Analyze existing IBM Netezza code and design migration solutions for AWS Data Lake
• Develop unit tests and support QA, SIT, and performance testing

  Required Skills & Experience

  • 12+ years of experience in data engineering/data warehousing
  • Strong experience in the banking and financial services domain
  • Hands-on expertise with Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift
  • Experience with AWS Step Functions, IAM, and CloudWatch
  • Strong ETL/ELT and data pipeline development experience
  • Experience with IBM Netezza and migration to AWS environments
  • Knowledge of Kafka, Spark, and batch data processing
  • Strong understanding of data warehouse architecture and data lake solutions

  Good to Have

  • AWS Solutions Architect or Data Analytics certification
  • Experience with Airflow or Amazon MWAA
  • Exposure to Snowflake, Databricks, or Delta Lake
  • Experience with CI/CD and cloud deployment practices