City : Toronto

Category : Full time

Industry : Public Services/Utilities

Employer : Healthcare of Ontario Pension Plan (HOOPP)

Why you’ll love working here:

• high-performance, people-focused culture

• our commitment that equity, diversity, and inclusion are fundamental to our work environment and business success, which helps employees feel valued and empowered to be their authentic selves

• learning and development initiatives, including workshops, Speaker Series events and access to LinkedIn Learning, that support employees’ career growth

• membership in HOOPP’s world class defined benefit pension plan, which can serve as an important part of your retirement security

• competitive, 100% company-paid extended health and dental benefits for permanent employees, including coverage supporting our team's diversity and mental health (e.g., gender affirmation, fertility and drug treatment, psychological support benefits of $2,500 per year, parental leave top-up, and a health spending account).

• optional post-retirement health and dental benefits subsidized at 50%

• yoga classes, meditation workshops, nutritional consultations, and wellness seminars

• the opportunity to make a difference and help take care of those who care for us, by providing a financially secure retirement for Ontario healthcare workers

Job Summary

The Senior Data Engineer is responsible for designing, implementing, and optimizing scalable data architectures and pipelines to support business objectives. This role requires collaboration with enterprise architecture teams, cross-functional stakeholders, and junior engineers to build robust data solutions. The engineer will manage and optimize data storage, processing, and querying in AWS S3 and Snowflake, drive automation initiatives, and ensure data quality, governance, and security compliance. Additionally, the role involves monitoring and troubleshooting data systems while contributing to release planning and backlog management.

What you will do:

• Build and maintain scalable, robust, and high-performance data architectures: This involves designing and implementing data systems that can handle large volumes of data efficiently and reliably.

• Collaborate with Enterprise Architecture team to ensure alignment to enterprise standards: Working closely with the architecture team to ensure that data solutions adhere to the company's standards and best practices.

• Collaborate with cross-functional teams to gather and define data requirements and translate them into technical solutions: Engaging with various teams to understand their data needs and translating those requirements into effective technical solutions.

• Manage and optimize data storage, processing, and querying in AWS S3 and Snowflake: Handling data storage and processing tasks using AWS S3 and Snowflake, ensuring optimal performance and efficiency.

• Drive automation of the platform for Infrastructure as Code (IaC) and CI/CD capabilities: Implementing automation processes for infrastructure management and continuous integration/continuous deployment.

• Design, implement, and optimize scalable data pipelines using AWS native tools, SageMaker Unified Studio, and Snowflake: Creating and optimizing data pipelines to ensure smooth data flow and processing.

• Update ETL procedures to ensure Data Quality rules are configured as defined in the data contracts and work with the Enterprise Data Platform Operations team to ensure data quality incidents and concerns are addressed in a timely manner for business users

• Assist the Enterprise Data Platform team with alignment to governance standards for access management and subscription processes, ensure domain definitions are aligned to governance practices

• Participate in design sessions, code reviews, and support the use of End User Compute on the Enterprise Data Platform

• Develop standards, patterns, and practices to improve Business Intelligence and use of Business Intelligence tools such as Power BI within the Enterprise Data Platform

Data Catalog Implementation

• Set up and configure connectors to data systems, workflows, and automations based on use cases

• Leverage personalization capabilities to ensure the catalog’s interface is user-friendly and aligned with user needs

• Design scalable and secure data architectures to support the catalog (e.g. integration and connectivity methodology between the catalog and data platform systems)

• Set up integrations with existing tools (Github, Teams) and adhere to established deployment processes.

• Managing migration of data platform systems with accuracy and minimizing downtime and impact to the catalog (w.r.t metadata completeness and accuracy)

• Technical curation of data assets for technical meta data, technical data quality and alignment of data products to medallion architecture

• Ensure the Data Marketplace is up to date with the latest data assets and data products, by troubleshooting any issues in data publication or data pipeline processes

Data Catalog Technical Maintenance

• Providing ongoing technical support and platform maintenance (workflows, integrations, automations etc.) post-implementation and managing performance, security, and scalability of the catalog and its integrations

• Diagnose production issues spanning the Enterprise Data Platform and Data Catalog, and work with the vendors to perform upgrades and/or maintenance

Working with Business Stakeholders

• Work closely with business users to review and validate data contracts, understand business data context, and ensure usability of the onboarded data to the data catalog

• Partner with the business team to ensure alignment on enterprise data governance policies and standards, provide guidance to end users on implementation of best practices

• Assist business users in maintenance of data catalog technical configurations, including data dictionary, data asset configurations, meta data, data products creation and medallion architecture

• Work with the internal IT/EDP team to ensure catalog domains/integrations/connectors are configured and maintained

• Promote data literacy to business and IT teams, and ensure use of data within the Enterprise Data Platform is in alignment with governance processes and architecture standards

What you bring:

• 7+ years in proven hands on experience in Data Engineering domain data platforms or backend engineering

• Strong experience working with cloud-based data platforms, preferably AWS

• Hands-on experience with AWS Glue, Athena, Python, and SageMaker or similar data processing and analytics services

• Solid experience with Snowflake for data warehousing and analytics

• Strong problem-solving skills with a focus on automation including CI/CD and IaC, DevOps practices, and version control, using tools like Azure DevOps and GitHub

• Proficiency in SQL, Pythonand experience in data modeling & performance optimization

• Experience building analytics in Power BI and analytics tools

• Experience in data validation, cleansing, and quality checks to maintain data integrity.

• Knowledge of data governance, security, and compliance best practices using tools such as SageMaker and Atlan

• Familiarity with data cataloging concepts, data governance, and meta data management

• Understanding of data governance frameworks, including roles like data stewards, data custodians, and data owners.

• Excellent communication and collaboration skills to work with stakeholders and teams.

The actual base salary offered to the successful candidate may vary based on multiple factors including, but not limited to, individual's expertise and level of experience applicable to the role they are being offered.  

This role is eligible to participate in discretionary incentive plan(s), subject to the terms and conditions of the applicable incentive plan text.