Role Description We are looking for a Data Architect to join our growing team! - Proven experience designing enterprise-scale data architecture. - Strong experience designing enterprise data architecture solutions, including: - Data models - Integration patterns - Platform architecture - Scalable data pipeline frameworks - Hands-on experience with cloud platforms such as AWS, Azure, OCI, or GCP, with the ability to design scalable and secure cloud-based data solutions. - Good understanding of modern data management platforms and solutions such as: - Databricks - Snowflake - Cloud data lakes - Lakehouse platforms - Similar technologies - Ability to define and implement data architecture standards, patterns, and best practices across: - Ingestion - Transformation - Storage - Consumption - Analytics layers - Strong understanding of data governance, including: - Data quality - Metadata management - Lineage - Access controls - Privacy - Security - Compliance requirements - Experience with Medallion Architecture and modern data engineering patterns, including bronze, silver, and gold layers for reliable and reusable data products. - Ability to partner with engineering teams on data pipeline design, performance optimization, autoscaling, CI/CD, DevOps, Terraform, Azure DevOps, and infrastructure-as-code practices. - Strong solutioning skills with the ability to translate business and technical requirements into scalable, secure, and cost-effective data platform solutions. Benefits - Be a part of a company that supports diversity and inclusion in the workplace. - Local and global opportunities for internal rotation and international mobility. - Clear view of your career progression with the company. - Flexible and casual culture with employee events and amenities. - 401k plan with company match to accelerate your savings plan. - Competitive healthcare benefits with HSA matching. - Access to Qualitest Tech Academy with 3000+ training courses, mentorship programs, and leadership programs. - Corporate Wellness Program that pays for gym memberships and offers additional vacation time for attendance. - Salary of $160,000 - $170,000 annually. - Bonuses via Client Referral and Employee Referral Programs. - Access to Qualitest Employee Perks for discounts on travel, electronics, and more.

Role Description As a senior member of the Data Engineer team, you will be responsible for leading the design, development, and optimization of enterprise-grade data solutions within the Microsoft Fabric ecosystem. This role requires deep technical expertise, strategic thinking, and the ability to mentor junior engineers while collaborating with cross-functional teams. You will work closely with data scientists, analysts, and other stakeholders to ensure seamless data integration, transformation, and storage, enabling data-driven decision-making across the organization. What you’ll do: - Design and orchestrate complex integrations across Data Factory, REST APIs, and other enterprise data services. - Lead scalable ELT strategies using Spark Notebooks, Data Factory, and Synapse Pipelines. - Architect multi-domain Lakehouse environments, including structure, metadata, and governance standards. - Optimize Data Warehousing workloads and configure performance settings for high-throughput environments. - Design enterprise-grade data models and refresh strategies for scalable, governed Power BI reporting. - Define and enforce modeling standards and best practices across engineering and analytics teams. - Develop reusable, optimized Spark jobs and configure compute pools for cost-efficient performance. - Establish naming conventions, workspace governance, and CI/CD deployment strategies across Fabric. - Lead data governance frameworks, including sensitivity classifications and access-control standards. - Build monitoring dashboards, alerts, and automated testing for Fabric pipelines and operations. - Demonstrate expert-level platform knowledge with the ability to troubleshoot, automate, and optimize end-to-end Fabric solutions. - Partner with architects, data scientists, and business stakeholders to align technical strategy with business needs. - Mentor engineers, review notebooks and data models, and drive adoption of Microsoft Fabric best practices. - Align Microsoft Fabric capabilities with enterprise data strategy, roadmaps, and long-term growth plans. - Lead cross-team data initiatives and influence architectural direction, governance decisions, and platform evolution. - Leverage AI coding agents and AI-assisted development tools (e.g., GitHub Copilot, Windsurf, or similar) to accelerate data engineering workflows, automate repetitive tasks, and improve code quality across the Fabric ecosystem. - Author and review advanced DAX measures, calculated columns, and time-intelligence logic to support complex, governed Power BI semantic models. - Translate ambiguous business problems into clear technical requirements, adapting communication style to audiences ranging from executive sponsors to frontline analysts with varying levels of data literacy. Qualifications - 5+ years of experience with deep expertise across the Microsoft data ecosystem, including Microsoft Fabric, Data Factory, Spark, Synapse, and Power BI. - Proven ability to design and orchestrate complex data integrations, leveraging Data Factory, REST APIs, and other enterprise data sources. - Leadership in defining and executing scalable ELT strategies using Spark notebooks, Data Factory, and Synapse pipelines. - Experience architecting multi-domain Lakehouse environments, with strong governance around structure, metadata, and reuse. - Advanced knowledge of data warehousing optimization, including performance tuning and workload configuration. - Expertise in designing scalable Power BI semantic models, refresh strategies, and governed reporting solutions. - Ability to define and enforce data modeling standards and best practices across multiple teams. - Strong skills in writing reusable, high-performance Spark jobs and configuring compute pools for optimal performance and cost efficiency. - Experience establishing naming conventions, workspace governance, and CI/CD deployment strategies. - Leadership in data governance, including sensitivity classifications, security models, and access control frameworks. - Ability to build and maintain monitoring, alerting, and automated testing for Fabric pipelines and data assets. - Expert-level understanding of the Fabric platform, with the ability to troubleshoot, automate, and optimize end-to-end solutions. - Strong partnership skills, collaborating with architects, data scientists, and business stakeholders to align technical solutions with business goals. - A passion for mentoring and technical leadership, including code reviews, model reviews, and driving adoption of new Fabric capabilities. - Ability to align Microsoft Fabric implementations with enterprise data strategy and long-term growth plans. - Hands-on experience using AI coding agents and AI-assisted development tools in a data engineering context; comfort integrating AI into daily development workflows and evangelizing adoption across the team. - Advanced DAX proficiency, including complex measure authoring, calculation groups, and optimization techniques for large-scale Power BI semantic models. - Strong business acumen with a genuine interest in understanding business domains, KPIs, and decision-making processes. - Preferred Microsoft Fabric certification – DP600, DP700. - Proven experience leading cross-team data initiatives, influencing platform architecture and governance direction. - Strong problem-solving skills and ability to work in a collaborative environment. - Excellent verbal, written, communication, presentation, organizational, and interpersonal skills. Compensation A reasonable estimate of the current base pay range for this position in Ontario is $91,200 to $114,000 annually. Actual salary will be based on a variety of factors, including location, experience, skill set, education, and related certification. The range for this position in other geographic locations may differ. Benefits - Health and Wellbeing: Medical and Dental Care, Employee & Family Assistance Program. - Financial Benefits: RRSP/DPSP Retirement Savings Plan with Company Matching, Life and Disability Insurance. - Paid Time Off: Vacation and Sick Leave, Holidays, Parental Leave, Volunteer Days, Bereavement Leave. - Additional Perks: Employee Discount Program.

Role Description This role is responsible for performing quality testing on all benefit plans. The position works closely with the AIS team throughout the plan‑build process to ensure each plan is configured accurately and meets client specifications. - Review plan setups across multiple systems. - Identify issues such as incorrect deductibles, out‑of‑pocket amounts, or mail pricing discrepancies. - Partner with AIS counterpart to resolve errors found. - Requires a high level of attention to detail. - No phone work; communication is limited to internal collaboration with team members and AIS representatives. - After training, measured through a scorecard; expected to complete approximately 25 plan reviews per week. - This is a non‑IT role within the Operations organization. Qualifications - Bachelor or Associates degree required. - 1+ year of Excel experience filtering through large sets of data. - 3+ years of health insurance preferred. - Medical terminology & provider language knowledge is preferred. - Experience in a production-based environment is a plus. - Not looking for someone coming from call center or QA in call center. Requirements - Start: 7/6 - Pay: $24.00/Hr - Schedule: Must be available for an 8-Hour shift Monday - Friday between 7:00am - 6:00pm CST. - Must be available during Peak Season Mandatory OT weekends between October - December. - Location: 100% Remote. Equipment will be provided. - Duration: Contract through the end of the year. Benefits - Medical, dental & vision. - Critical Illness, Accident, and Hospital. - 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available. - Life Insurance (Voluntary Life & AD&D for the employee and dependents). - Short and long-term disability. - Health Spending Account (HSA). - Transportation benefits. - Employee Assistance Program. - Time Off/Leave (PTO, Vacation or Sick Leave). Application Deadline This position is anticipated to close on May 12, 2026.

Role Description The Central Data Team (CDT) is only a few months old, but data has been Keyrock's lifeblood since day one. We're now building the Keyrock Data Platform to give Keyrockers, and the AI agents working alongside them, the data and context they need to act fast and autonomously within agreed boundaries and aligned with our shared goals. Doing that means taking data from across the company and making sense of it in real time for all the functions that depend on it: trading desks, wealth and asset management, product, risk, finance, compliance, and research to name a few. You'd be one of the early hires in CDT and we expect you to contribute to most of the bigger decisions and build work. The standards we settle on and the way the team ends up working are still open. - Build streaming and batch pipelines that ingest, normalise, and distribute market, trading, and portfolio data, resilient to feed and exchange failures. - Build the self-serve tooling (SDKs, patterns, templates, AI agents) so other teams publish, consume, and build on data products without waiting on us. - Own data contracts and schema evolution. Keep schema changes from turning into multi-team coordination events. - Design the lakehouse and time-series layer around consumer query patterns. - Build and evolve the Data Governance and Data Quality Framework: stale-feed detection, schema validation, range checks, idempotent writes, lineage, ownership, self-healing. - Build the derived analytics the business runs on: cross-exchange spreads, VWAP at depth, order book microstructure for the desks; portfolio views, exposure, performance for wealth and asset management. - Make observability, cost, and performance first-class from day one. - Treat infrastructure as code (Docker, Terraform, CI/CD) alongside our Central Infrastructure Team. - Work in the open: write things down, partner closely with Architecture, Infrastructure, Platform, and the rest of the teams. Qualifications - 8+ years of building production data systems that other people rely on. - Strong proficiency in Python and SQL: not just being able to write a query, but being able to reason about what the engine is doing with it. - Code that's easy for someone else to read, test, and delete later. - Strong understanding of data modelling for both streaming and analytical workloads. - Efficiency, quality, idempotency, and observability are taken seriously by default. Requirements - You've designed and operated streaming systems on Kafka, Redpanda, MSK, or Kinesis, and you have opinions about partitioning, consumer groups, offsets, and schema registries. - You've used a time-series store in production (ClickHouse ideally; TimescaleDB, QuestDB, or similar are fine too) and can talk about table design as a function of query patterns. - You've worked with a lakehouse architecture and reason about table layout, partitioning, and compaction as design choices that shape query performance and storage cost. - You build for self-healing and idempotency. Reprocessing is safe, retries don't double-write, and the system recovers without a human in the loop. - Docker, Terraform, and CI/CD are how you work, not a separate "DevOps" thing. - You think about cost and performance early. - You instrument as you build: logs, metrics, and traces are part of the system from day one. - You design for data quality and governance up front covering contracts, validation, lineage, and ownership. Nice to Have - Lakehouse experience with Apache Iceberg or Delta Lake. - Familiarity with DataHub or similar metadata/lineage platforms. - Rust. Some of our performance-critical services are written in it. Interest is welcome; fluency isn't required. Benefits - A from-scratch mandate. You'll be among the first hires in CDT, and the platform, the standards, and the team culture are yours to shape with us. - Strong partners. Close working relationships with Architecture, Infrastructure, Platform, and the desks themselves. You won't be building data in a vacuum. - Autonomy on how you work. Flexible hours, remote-first, business-hours on-call shared across the team. - A competitive salary package, with various benefits. - A team that likes each other. Regular online get-togethers and a yearly onsite where everyone's in the same room. Company Description Since our beginnings in 2017, we've grown to be a leading change-maker in the digital asset space, renowned for our partnerships and innovation. Today, we partner with over 250 team members around the world. Our diverse team hails from 42 nationalities, with backgrounds ranging from self-taught DeFi natives to PhDs. Predominantly remote, we have hubs in London, Brussels, and Singapore, and host regular online and offline hangouts to keep the crew tight. We are trading on more than 80 trading venues, and working with a wide array of asset issuers. As a well-established market maker, our distinctive expertise led us to expand rapidly. Today, our services span market making, options trading, high-frequency trading, OTC, and DeFi trading desks. But we’re more than a service provider. We’re an initiator. We're pioneers in adopting the Rust Development language for our algorithmic trading, and champions of its use in the industry. We support the growth of Web3 startups through our Accelerator Program. We upgrade ecosystems by injecting liquidity into promising DeFi, RWA, and NFT protocols. And we push the industry's progress with our research and governance initiatives. At Keyrock, we're not just envisioning the future of digital assets. We're actively building it.