Reports to Chief Technology Officer (CTO)

Job Summary:

- As a Software Engineer working on our data platform, you’ll design, build and operate the data systems that support our products, analytics, and internal teams.
- This role sits at the intersection of software engineering, data engineering, and platform infrastructure. You’ll be responsible for the reliability, scalability, and evolution of our data platform – from operational databases and ingestion pipelines, through transformation, analytics, and reporting systems.
- You’ll work closely with engineering, product, QA, and business stakeholders to ensure that data is accurate, secure, accessible, and useful across the organization.

What You’ll Do:

- Design, build, and maintain scalable data infrastructure and data pipelines.
- Own and evolve the architecture supporting operational, analytical, and reporting workloads.
- Develop reliable ingestion, transformation, and data-processing workflows across multiple systems and data sources.
- Maintain and optimize relational and NoSQL databases, including PostgreSQL and MongoDB.
- Establish and improve standards for data quality, validation, lineage, observability, and reliability.
- Monitor data pipelines and infrastructure, investigate failures, and improve resilience and recoverability.
- Design data models and storage strategies that balance performance, scalability, maintainability, and cost.
- Build and maintain integrations between product systems, data platforms, analytics tools, and external services.
- Support analytics and reporting platforms such as Power BI by providing well-structured, reliable datasets.
- Apply appropriate security controls to data systems,



including access management, encryption, data isolation, retention, and handling of sensitive information.
- Partner with application and platform engineers to define efficient approaches for generating, storing, querying, and consuming data.
- Improve database and query performance through indexing, schema design, query optimization, and capacity planning.
- Help define engineering standards and best practices for data architecture and data engineering across the organization.
- Participate in technical design reviews and contribute to broader Platform architecture decisions.
- Mentor other engineers and provide technical guidance on database, data pipeline, and data architecture topics.

What We’re Looking For:

- Solid professional software engineering experience, including experience designing and operating production systems.
- Significant experience building and maintaining data pipelines and data infrastructure.
- Strong knowledge of relational databases and SQL, including schema design, indexing, query optimization, and performance troubleshooting.
- Experience with PostgreSQL or similar relational database platforms.
- Experience with document or NoSQL databases such as MongoDB.
- Experience designing data models for both operational and analytical use cases.




- Familiarity with distributed data-processing or big-data technologies such as Apache Spark.
- Experience supporting analytics and business intelligence platforms such as Power BI.
- Experience working with cloud infrastructure and managed data services in AWS, Azure, or similar environments.
- Understanding of data security principles, including authentication, authorization, encryption, data classification, and least-privilege access.
- Experience building observable and reliable data systems, including monitoring, alerting, logging, and failure recovery.
- Strong understanding of software engineering practices including source control, automated testing, CI/CD, code review, and infrastructure as code.
- Ability to communicate technical concepts clearly and collaborate across engineering and non-engineering teams.

Nice to Have:

- Experience with data warehouses, data lakes, or lakehouse architectures.
- Experience with change data capture, event-driven architectures, or streaming data platforms.
- Experience with technologies such as Kafka, Airflow, dbt, Databricks, or equivalent tooling.
- Experience designing data governance, lineage, retention, or lifecycle-management practices.
- Experience managing high-volume transactional or event data.
- Experience with containerized and cloud-native infrastructure.
- Experience supporting data platforms used across multiple products or engineering teams.

What Success Looks Like:

- In this role, you will help establish a dependable data foundation for the organization. Our data pipelines and platforms should be observable, maintainable, secure, and able to scale as our p

📌 Data Engineer (Toronto)
🏢 TimePlay
📍 Toronto