Summary:

We are currently seeking aSenior Data Platform Engineer to join our rapidly growing Security team and help grow our Logging Engineering team. This role is for someone passionate about building scalable logging architectures, designing robust data pipelines, and driving security-focused logging automation at scale. You will help lead, support, and implement the technical architecture for our logging infrastructure while making a tangible impact on our security observability.

This role is available to candidates across Canada. If you are local to one of our hubs (Burnaby, Calgary, or Toronto) you will be expected to be in office minimum two days per week for our Anchor Days.

What your team does

Are you someone who's always probing and asking why, someone who enjoys architecting elegant solutions to complex data pipeline challenges? If so, we have a spot for you on Clio's Logging Engineering team! We are looking for candidates to help design and evolve our logging platform architecture, supporting the team with technical leadership for security logging overall. If you have a strong data engineering background with a passion for security and experience building enterprise-scale logging platforms, then we want to talk to you.

A day in the life might look like:

• Contributing to the design and architecture of scalable logging infrastructure including data lakes, security lakes, and multi-tier storage strategies
• Building and optimizing high-throughput log ingestion pipelines using streaming technologies and cloud-native services
• Architecting ELK stack deployments, OpenSearch clusters, and hybrid cloud logging solutions
• Designing data retention, lifecycle management, and cost optimization strategies for petabyte-scale log storage
• Partnering with the security team lead to develop the logging platform roadmap and technical vision
• Building Infrastructure as Code for logging infrastructure provisioning, scaling, and disaster recovery
• Optimizing query performance across multiple data stores and implement efficient data partitioning strategies
• Designing API and integration layers for log data access, enabling self-service analytics and detection engineering
• Contributing to capacity planning, performance tuning, and architectural decisions for the logging platform
• Mentoring engineering team members on logging best practices, data architecture, and platform operations

What you may have:

• Proven Senior-level expertise building enterprise-scale logging and data ingestion systems, typically gained over 5+ years of relevant experience
• Data architecture experience designing data lakes, lake houses, and multi-tier storage architectures for log data
• Mastery of big data technologies and processing systems including but not limited to Splunk, OpenSearch, ElasticSearch & the ELK Stack, Map Reduce, Hadoop, Cassandra, and other comparable data ingestion & query systems
• Experience in Data Modelling using one or more methodologies like Kimbal, Inmon, or Data Vault for data-at-rest schema normalization
• Streaming data expertise with Apache Kafka, Amazon Kinesis, AWS Glue, Azure Event Hubs, or similar real-time ingestion platforms
• Cloud storage architecture experience with AWS S3, Azure Data Lake, GCS, and intelligent data tiering strategies
• Performance optimization skills for high-volume data ingestion, indexing strategies, and query optimization
• Infrastructure as Code proficiency with Terraform, CloudFormation, or similar for logging infrastructure automation
• Data pipeline engineering experience with Apache Spark, Flink, or cloud-native data processing services
• API and integration design for enabling secure access to log data across multiple consumer applications
• Monitoring and observability expertise for logging platform health, performance metrics, and capacity planning
• An AI first mentality, where your decision making, coding, and throughput are amplified through your AI usage

Serious bonus points if you have:

• Programming proficiency in Python, Ruby, Go, or Scala for custom logging pipeline development and automation
• Experience with SQL Data Warehouse Dimensional Modelling using Kimball, Inmon, Business Data Vault or other modelling techniques.
• Kubernetes and Container encapsulation for logging architecture within cloud-native application systems.
• Security-focused logging experience with SIEM integration, security data lakes, and compliance-driven data retention
• Multi-cloud logging architecture designing consistent logging platforms across AWS, Azure, and GCP
• Data governance expertise implementing data classification, privacy controls, and regulatory compliance for log data
• Advanced analytics platforms experience with Splunk Enterprise, Sumo Logic, or other enterprise logging platforms
• Cost optimization expertise for large-scale data storage, implementing intelligent archiving and data lifecycle policies
• Technical leadership experience mentoring teams, setting architectural standards, and driving technical strategy

This role is a backfill for an existing position.
What you will find here:

Compensation is one of the main components of Clio's Total Rewards Program. We have developed a series of programs and processes to ensure we are creating fair and competitive pay practices that form the foundation of our human and high-performing culture.

Some highlights of our Total Rewards program include:

• Competitive, equitable salary with top-tier health benefits, dental, and vision insurance
• Hybrid work environment, with expectation for local Clions (Vancouver, Calgary, Toronto, Dublin, London, New York City and Sydney) to be in office min. twice per week.
• Flexible time off policy, with an encouraged 20 days off per year.
• $2000 annual counseling benefit
• RRSP matching and RESP contribution
• Clioversary recognition program with special acknowledgement at 3, 5, 7, and 10 years

The expected salary range for this role is $157,300 to $212,800 CAD. Initial placement within the range is informed by geographic region, experience, and skillset, with room to progress as impact and tenure grow. Final offer amounts will vary based on candidate profile.