Posted 17 days ago
Data Engineer
@ TimePlay
Toronto, Ontario
Overview
TimePlay is hiring a Data Engineer in Toronto on a hybrid arrangement to design, build and operate the data platform that supports its products, analytics and internal teams. The role covers data pipelines, databases, data quality and security, reporting to the Chief Technology Officer. The posting asks for strong software engineering and data engineering experience and does not state a salary.
Responsibilities:
- Design, build and maintain scalable data pipelines and infrastructure
- Maintain and optimize PostgreSQL and MongoDB databases
- Establish data quality, validation and observability standards
- Apply data security controls including access management and encryption
- Support Power BI analytics with well-structured datasets
Requirements summary:
- Significant experience building data pipelines and infrastructure
- Strong SQL and relational database knowledge
- Experience with PostgreSQL and MongoDB
- Experience with Apache Spark or similar big-data tools
- Cloud data services experience in AWS, Azure or similar
- Solid software engineering practices including CI/CD and infrastructure as code
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-10-27
- First seen by our source
- 2026-11-14
- Source record updated
- 2026-11-14
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Data & analytics |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
TimePlay
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 [email protected]
Subject - Software Engineer (DATA)
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