What’s in it for you as an employee of QFG? Health & wellbeing resources and programsPaid vacation, personal, and sick days for work-life balanceCompetitive compensation and benefits packagesWork-life balance in a hybrid environment with at least 3 days in officeCareer growth and development opportunitiesOpportunities to contribute to community causesWork with diverse team members in an inclusive and collaborative environment We’re looking for our next Senior Cloud Data Platform Engineer. Could It Be You?At Questrade, we exist for one reason: to help Canadians grow and protect their wealth. Every system we build, every pipeline we design, every stream we process — it all connects back to that promise. When a trade executes in milliseconds or a client sees their portfolio update in real time, that is not just infrastructure. That is their financial future, delivered. The Questrade Enterprise Shared Services (Quest Corp) is where this happens. We operate across a hybrid cloud environment spanning our own data centres and Google Cloud Platform, and we move fast by design. We are not here to process transactions and go home. We are on a mission. The Senior Cloud Data and Streaming Platform Engineer joins a team at the heart of our real-time data infrastructure. This is a niche role for someone who genuinely cares about low-latency, high-throughput data systems — someone who knows Kafka not just as a technology, but as a craft. You will own the streaming backbone that powers Questrade's market data, event-driven architectures, and operational analytics, and help shape how Change Data Capture (CDC) and OLAP technologies like ClickHouse scale to meet the demands of a growing fintech company that serves millions of Canadians. Nothing you build here is small. The pipeline you design today may be the infrastructure that helps a Canadian family invest confidently tomorrow. We are looking for a Senior Cloud Data Platform Engineer with deep, hands-on expertise in real-time streaming systems, Change Data Capture, and columnar OLAP databases. This is not a generalist data engineering role — we need someone who has operated Kafka at scale, built robust CDC pipelines, and knows how to tune ClickHouse for production workloads. You will work alongside Software Engineers, Data Scientists, and Product teams to build the streaming infrastructure that underpins Questrade's core products and Digital Banking initiatives. You will bring ownership to your work — if you see something broken or missing, you will not wait for a ticket. You will think about the client on the other end of the data stream and hold yourself to a standard you would be proud to defend. This role rewards people who are lit up by hard problems, who treat failure as information, and who understand that "growth is non-negotiable" applies to the platform as much as it does to the people who build it. At Questrade, if this year looks exactly like last year, something has gone wrong. Need more details? Keep reading… Design, build, and operate high-throughput, low-latency Kafka streaming pipelines for market data, transactional events, and operational telemetry Architect and implement Change Data Capture (CDC) solutions using Debezium, Kafka Connect, and related tooling to enable real-time data synchronization across operational and analytical systems Build, tune, and maintain ClickHouse OLAP clusters — including schema design, materialized views, MergeTree engine family selection, distributed query optimization, and data compression strategies Create and maintain optimal data pipeline architecture across streaming and batch workloads Design and create new features and automated solutions that meet functional and non-functional business requirements Identify, design, and implement internal process improvements: automating manual processes, implementing data governance rules, re-designing infrastructure for greater scalability Maintain in-depth understanding of data protection and network security rules on Cloud Infrastructure Monitor and manage Kafka cluster health, consumer lag, throughput, schema governance (Schema Registry), and topic lifecycle management Expand and increase data platform capabilities to resolve new streaming data problems by identifying, sourcing, and integrating new features and technologies Work with stakeholders to support data-related technical issues and data infrastructure needs Peer review code and promote DevOps culture within the data teams Apply ownership in practice: if you see a problem in the platform, do not wait for it to be assigned — awareness is the first act of responsibility Explore AI integrations into the Data Engineering development cycle Have a good understanding of data platform best practices to achieve economies of scale, cost reduction, and efficiencies. So are YOU our next Senior Cloud Data Platform Engineer? You are if you have… Minimum 3+ years of data engineering experience, with at least 2 years focused on streaming and event-driven architectures Strong expertise in Apache Kafka: cluster operations, topic design, Kafka Connect, Kafka Streams, Schema Registry (Avro/Protobuf), consumer group management Hands-on experience with Change Data Capture (CDC) patterns and tooling — particularly Debezium, Kafka Connect CDC connectors, Datastream and event sourcing principles Experience with ClickHouse: MergeTree engine family, materialized views, distributed table design, query optimization, compression codecs, and performance tuning for real-time analytics Proficiency in SQL (including ClickHouse SQL dialect) and Python Experience with any of the major cloud platforms (GCP preferred; AWS or Azure also considered) GCP data platform knowledge is a strong asset: Dataflow, Dataproc, Cloud Pub/Sub, Cloud Composer, BigQuery, CloudSQL Strong knowledge of message broker and streaming systems (Kafka, Google Pub/Sub, Kafka MirrorMaker) Experience with CI/CD pipeline tooling and development practices Experience building Terraform scripts for infrastructure-as-code Good knowledge of Airflow operators and DAG configuration Good knowledge of popular data standards and formats (JSON, Avro, Protobuf, Parquet, ORC) Experience with stream processing frameworks (Apache Flink, Spark Structured Streaming, or GCP Dataflow) is a strong asset Data modeling skills with experience in both streaming and batch paradigms Experience with OLAP databases beyond ClickHouse (BigQuery, Druid, Redshift) is a plus Experience with ML Model Training using Google Vertex AI is an asset Experience in the financial services industry is an asset Compensation Information: Base salary range: $130,000 - $150,000 The final compensation package will be commensurate with the successful candidate's experience, skills, and geographic location (Canada). It includes a comprehensive benefits plan and a competitive incentive (bonus) program for Full-Time Permanent roles. Sounds like you? Click below to apply! #LI-Hybrid #LI-CE1