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A leading technology company in Toronto is seeking a Senior Data Engineer to architect robust data pipelines and facilitate the evolution of legacy systems. This role requires significant expertise in AWS and technical mentorship of engineering teams. The ideal candidate will have a strong background in data architecture, excellent problem-solving skills, and the ability to collaborate across teams. Competitive compensation is offered, aligned with experience and market demands.
Who we are looking for:
In this senior technical role for ACVMax, you will architect and deliver robust data pipelines, warehouses, and lakes that enable advanced analytics, machine learning, and business intelligence at scale. You will set technical direction, mentor engineering teams, and ensure best practices for performance, security, and cost-effectiveness in our cloud-based data ecosystem. You will collaborate with cross-functional teams to deliver high-quality, robust, and scalable solutions that empower our customers to manage and analyze their data effectively. You will have deep expertise in designing, building, and optimizing modern, scalable data platforms on AWS, MS SQL Server and MongoDB. You will set technical direction, mentor engineering teams, and ensure best practices for performance, security, and cost-effectiveness in our cloud-based data ecosystem.
Our goal is evaluate, plan, and execute the evolution of our legacy data architecture to a more modern approach, allowing deprecation of legacy applications and empowering our new SaaS solutions.
What you will do:
Design and implement end-to-end data architectures on AWS, including data lakes, data warehouses, real-time streaming pipelines, and ETL/ELT processes.
Very strong data engineering experience working with AWS Tech Stack with a focus on building complex self healing data engineering pipelines, cloud delta lakes and migrating legacy technology stack to the Cloud
Extensive experience with reverse engineering legacy stored procedures into data pipelines built using AWS Glue would be an added advantage
Lead the design of data models, storage solutions, and access patterns that support analytical and operational workloads. Deep understanding of data modeling in Postgres db environments. Ability to reverse engineer legacy data models and redesign with foundational architectural principles including normalization, cardinality and ACID into Postgres databases like Aurora is critical.
This role requires deep technical expertise, strong communication skills, and the ability to lead complex initiatives across multiple teams. Experience working on multiple projects simultaneously while troubleshooting technical issues and working with cross-functional stakeholders while communicating effectively to influence external engineering teams, product development teams, Business stakeholders and external partners.
Act as a trusted advisor to stakeholders, bridging business needs with technical execution, and ensuring best practices in cloud architecture, security, and cost optimization. Work closely with our application architects, data scientists and data engineering teams to develop, enhance and define new data integrations and BI solutions.
Mentor and guide engineering teams in implementing AWS services effectively and efficiently. Stay current with AWS service offerings and emerging cloud technologies, and recommend adoption where appropriate.
Optimize AWS workloads for performance, scalability and cost efficiency, leveraging tools like Trusted Advisor, Well-Architected Framework, and Cost Explorer.
Deep experience with services such as:
Storage & Compute: S3, EMR, Glue, Redshift, Athena, Lambda, EC2, EKS
Streaming & Messaging: Kinesis, Kafka, MSK, SNS/SQS
Orchestration & Workflow: Step Functions, Airflow, Data Pipeline
Databases: Aurora Postgres, MongoDB, MS SQL Server
Mentor and coach junior engineers, fostering a culture of technical excellence and continuous improvement to mature Data Engineering practices enterprise wide. Deliver TechTalks and training sessions on a regular basis.
Previous experience in the Auto Industry would be a significant added advantage
What you will need:
At least 7 or more years of experience working in the data engineering field as a Senior Data Engineer with at least 4 years designing and implementing solutions on AWS
Solid understanding of SaaS, distributed systems, scalability, and high availability concepts.
Previous experience mentoring junior data engineers, providing technical expertise, code reviews, and sharing best practices to foster professional growth.
Excellent problem-solving skills and the ability to navigate complex technical challenges.
Strong communication skills and the ability to collaborate effectively in cross-functional teams.
Experience with hybrid cloud and multi-cloud strategies
Familiarity with other cloud platforms (Azure, GCP)
Hands-on coding/scripting in Python, Bash, or similar
Compensation: $127,000.00 - $159,000.00 CAD annually. Please note that final compensation will be determined based upon the applicant's relevant experience, skillset, location, business needs, market demands, and other factors as permitted by law. #LI-AM1
No immigration or work visa sponsorship will be provided for this position. #LI-AM1