Data Engineer

Software Engineer (DATA)

Data Engineer

Reports to Chief Technology Officer (CTO)

Toronto. Hybrid

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:

• Strong 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 products grow.
• You will help make it easier for engineering and business teams to trust and use our data while reducing operational complexity and improving the overall quality of our data architecture.

Working Environment

• You’ll be working within a cross-functional team of software engineers, product, and business stakeholders, contributing to live products used in high-traffic, real-world environments.
• We emphasize automation, reliability, practical engineering, and continuous improvement as core to our engineering culture.

To Apply:

Please email your resume, cover letter and compensations expectations to careers@timeplay.com

Subject - Software Engineer (DATA)