AWS Senior Platform Engineer

Red Pico; Toronto; Hybrid; CAD 90,000 - 120,000; Full time

Job summary

A technology company is seeking an AWS Senior Platform Engineer to join its data engineering team. This remote position involves developing data pipelines, managing AWS services, and ensuring data quality. Ideal candidates have at least 5 years of relevant experience and strong skills in data engineering technologies. This role also supports hybrid work with two days per week onsite in North Vancouver.

Qualifications

• 5 years of experience in data engineering or platform engineering roles.
• Proficiency in writing robust data validation and quality checks.
• Experience developing and executing test cases for Big Data pipelines.

Responsibilities

• Design, develop and optimize data pipelines using EMR and Spark.
• Implement and manage AWS Lake Formation for secure data access.
• Contribute to the development of data mesh solutions.

Skills

Data engineering

AWS EMR

Spark (PySpark)

AWS Lake Formation

Data mesh architecture

Terraform

Data quality assurance

SQL

Tools

Hadoop

NoSQL

Scala

Tableau

Job description

Overview

This is a remote position. We are seeking a highly skilled and motivated AWS Senior Platform Engineer to join our growing data engineering team. This role is ideal for someone who thrives in a fast-paced environment and is passionate about building scalable secure and high-performance data platforms.

Location

Across Canada

Employment Type

Full Time

Status

Contract

Responsibilities

• Design, develop and optimize data pipelines using EMR and Spark (PySpark)
• Implement and manage AWS Lake Formation for secure and governed data access
• Contribute to the development and adoption of data mesh solutions enabling decentralized data ownership and interoperability
• Write and maintain data quality checks to ensure accuracy, completeness and reliability of data assets
• Build out data catalog solutions on AWS
• Support light DevOps tasks with a strong preference for experience in Terraform for infrastructure as code

Qualifications

• 5 years of experience in data engineering or platform engineering roles
• Strong hands-on experience with AWS EMR, Spark (PySpark) and Lake Formation
• Familiarity with data mesh architecture and its implementation in enterprise environments
• Proficiency in writing robust data validation and quality checks
• Experience working within structured frameworks and agile environments
• Exposure to DevOps practices especially using Terraform for provisioning and managing cloud infrastructure

• 5+ years of experience in data quality assurance and testing, including developing and executing functional test cases, validating data pipelines, and coordinating deployments from development to production environments
• Has supported at least one Enterprise / Government Organization with Big Data platforms and tools, such as Hadoop (HDFS, Pig, Hive, Spark), Big SQL, NoSQL, and Scala, ideally within cloud-based environments
• 3+ data analysis and modeling projects, including working with structured and unstructured databases, building automated data quality pipelines, and collaborating with data engineers and architects to ensure high data integrity
• Experience developing and executing test cases for Big Data pipelines, with deployments across dev, test, and production environments
• Strong SQL skills for validation, troubleshooting, and data profiling
• Applied knowledge of Big Data platforms including Hadoop (HDFS, Hive, Pig), Spark, BigSQL, NoSQL, Scala
• Familiarity with cloud data ingestion and integration methods
• Experience working with structured and unstructured data formats
• Understanding of data modeling, data structures, and use-case-driven design
• Experience in test automation for data validation pipelines is a strong asset
• Prior experience with Genesys Cloud testing is a plus
• Exposure to Tableau or other BI tools is beneficial
• Hybrid role: 2 days per week onsite in North Vancouver