Lantern is looking for a Senior Data Engineer to join our Data Engineering team. The ideal candidate will have an advanced knowledge of building Data Pipelines, batch processing frameworks, and Data Modeling techniques to facilitate seamless Data Ingestion and Exports. In this role you will collaborate with various technology and business stakeholders to deliver data solutions that meet user needs. The candidate should possess intellectual acumen, with an engineering mindset and an interest in developing enterprise scale solutions using industry recognized cloud platforms, databases, data integration/orchestration tools, and big data technologies.

Location: Hybrid - at least 3 days/wk in Vancouver, BC

Responsibilities:

• Design and implement robust, scalable, and high-performance data pipelines
• Implement Data Ingestion, transformation, and Data Quality features to support Application Engineering, Analytics, and various Business Verticals across the organization.
• Collaborate with Data Engineering Manager, and Product in building data models to improve reliability and interpretability of data for analytical and business needs.
• Design, develop, and maintain robust data export solutions to facilitate the efficient transfer of data to external systems and platforms.
• Actively contribute to the creation of design documents, assess technologies, and conduct Proof of Concepts (PoCs).
• Experience supporting production jobs and mitigate issues in a timely manner.
• Write unit, integration, and functional tests for new features.
• Contribute to the Technology Roadmap, PR Reviews and formulate standards/best practices.
• Bring in a positive attitude and foster a culture that embraces continuous learning and Innovation.

 Qualifications:

• 5+ years of experience as a Data Engineer, with a focus on building enterprise data solutions.
• 3+ years of experience with cloud and infrastructure on Azure (preferred), AWS, or GCP.
• Strong experience with Python, with ability to discuss design patterns; strong SQL skills.
• Expert in Microsoft SQL Server (preferred) or other relational databases.
• Expertise with SQL, stored procedures, triggers, and performance tuning.
• Experience working with big data technologies such as Spark (preferred), Databricks, or similar frameworks.
• Experience using Infrastructure as Code tools such as Terraform (or similar) to provision and manage cloud resources.
• Prior experience in building data pipelines that are scalable, reliable and fault tolerant while delivering data integrity and code quality.
• Experience in building data lakes to support high speed querying by the end users.
• Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
• Prior Experience working with Healthcare Information exchange standards like HL7, X12 EDI, FHIR will be helpful.
• Experience or knowledge of creating RESTful API’s is a plus.
• Experience building Dashboards and visualizations using Power BI or other tools is a plus.

Benefits

• Medical Insurance
• Dental Insurance
• Vision Insurance
• Short- & Long-Term Disability
• Life Insurance
• Flexible PTO
• RRSP with company match

The Data Engineering team’s mission is to ensure high-quality data to enable data-informed decision-making across Asana. You will build data artifacts that are leveraged by Product and Business Data Science teams to optimize our user adoption, growth, and experience. In this role, you will partner with the Infrastructure team to build a self-service analytics platform for the company. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday; most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve

• Design, implement, and scale end-to-end data products that support growing data processing and analytical needs
• Transform raw data into actionable insights to drive product strategy and power in-depth analyses and reporting
• Leverage AI to build self-serve tools and accelerate Data/GTM workflows
• Partner with data scientists, domain experts, and engineering teams to develop a roadmap that aligns with our business goals
• Implement systems that guarantee data quality, governance, and availability

About you

• 5+ years of experience in Data Engineering or Software Engineering
• Experience in data modeling and building scalable data pipelines involving complex transformations
• Proficiency in data processing and storage technologies like Databricks, AWS/S3, Python/Scala/Java, SQL, Spark, and Airflow
• Proactive and innovative in identifying and addressing performance bottlenecks in existing workflows
• Motivated to work closely with cross-functional partners to evolve our analytical data model
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making

At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.

What we’ll offer

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between CAD $138,000 - $168,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified. In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences

#LI-Hybrid

Data Platform Solution Architect

Who We Are: 

Quadbridge is a fast-growing North American IT solutions provider, empowering businesses to navigate complex challenges daily, through strong partnerships with leading technology providers and close collaboration with our team and customers.

With locations in Kitchener, Montreal and Vancouver, we strive to create an energetic, fun workplace where ambitious, like-minded teammates collaborate, innovate, and thrive as we continue to grow our national footprint.

We are Quadbridge. See how we’re building tomorrow’s solutions, together.

This Role:

We are seeking a mid‑level Data Platform Solution Architect to join our consulting and professional services team.

This role blends solution architecture, pre‑sales support, and delivery execution, focused on designing and implementing modern data and AI platforms using Microsoft Fabric and Azure Databricks.

The successful candidate will work closely with pre-sales & delivery teams to drive assessment‑led engagements, build scalable data platform & AI design and architectures, and accelerate customer outcomes while enabling downstream services and managed services attach.

Key Responsibilities

Solution Architecture & Design

• Architect modern Data & AI platforms (Lakehouse/Data Lake) and analytics platforms using:
• Microsoft Fabric (OneLake, Data Engineering, Data Factory, Data Science, Real‑Time Analytics, Power BI)
• Azure Databricks (Lakehouse, Delta Lake, Workflows, Unity Catalog)
• Design secure, scalable, and cost‑optimized Data & AI platform architectures aligned to SMB and mid‑market needs
• Develop reference architectures and repeatable patterns aligned to Microsoft and Databricks best practices

Pre‑Sales & Assessments

• Support pre‑sales activities including:
• Technical discovery sessions
• Architecture whiteboarding
• Scoping and estimation support for Statements of Work (SOWs)
• Lead or contribute to Data & AI platform assessments (Data & AI Readiness, Fabric Readiness, Databricks/Lakehouse Assessments)

Delivery & Technical Leadership

• Act as technical lead or senior contributor on data platform implementations
• Provide design oversight and hands‑on guidance for:
• Data ingestion pipelines
• Data source integrations
• Transformations (SQL, PySpark)
• Semantic models and analytics layers
• Ensure delivery aligns to scope, timelines, and architectural standards

Governance, Security & Optimization

• Design data governance, security, and compliance models including:
• Data access controls
• Cataloging and lineage
• Workspace and tenant design
• Apply FinOps and performance optimization practices to control cloud costs
• Advise clients on platform lifecycle management and operational readiness

Partner & Practice Enablement

• Stay current with Microsoft Fabric and Databricks roadmaps and partner best practice guidance
• Contribute to:
• Internal accelerators
• Delivery templates
• Sales enablement content
• Support partner motions aligned to Microsoft Solution Partner and Databricks designations

Required Qualifications

Technical Experience

• 4–6 years of experience in data & AI engineering, analytics, or data platform architecture
• Hands‑on experience with:
• Microsoft Fabric or strong Azure Data + Power BI background transitioning to Fabric
• Strong Copilot/Copilot Studio background
• Azure Databricks and or Databricks
• Strong understanding of:
• Data platform & AI Lakehouse architecture
• ELT/ETL patterns
• SQL and PySpark
• Experience with Azure data services such as:
• Azure Data Lake Storage
• Azure Synapse
• Azure SQL
• Azure Data Factory

Consulting & VAR Experience

• Experience in a VAR, systems integrator, or consulting environment

Communication & Collaboration

• Strong client‑facing consulting and communication skills
• Ability to translate technical concepts into business value
• Experience collaborating with sales, delivery, and pre-sales teams

Preferred Certifications

Microsoft (preferred)

• Microsoft Certified: Fabric Analytics Engineer Associate
• Microsoft Certified: Azure Data Engineer Associate
• Microsoft Certified: Azure Solutions Architect Expert (plus)

Databricks

• Databricks Data Engineer Associate
• Databricks Data Engineer Professional
• Databricks Lakehouse Fundamentals

Cloud & Architecture (Nice to Have)

• Azure Fundamentals (AZ‑900)
• AI‑900 (Azure AI Fundamentals)
• FinOps Practitioner (or equivalent cost‑management training)

What Success Looks Like (First 12 Months)

• Successfully support and deliver multiple Fabric and Databricks engagements
• Become a trusted technical advisor to sales and clients
• Drive assessment‑led opportunities into implementation and managed services
• Contribute to repeatable offerings that improve delivery margin and velocity

Why Quadbridge? 

• Invest in Your Future – Benefit from our RRSP program to help you plan ahead.
• Grow With Us – Take advantage of ongoing professional training and development opportunities.
• Comprehensive Coverage – A complete health, dental, life and LTD insurance plan
• Top-Tier Equipment – We provide everything you need to do your best work.
• A Vibrant Workplace – Join us for monthly social and team building events.
• Perks You’ll Love – In our Montreal office, enjoy an onsite chef and gym.
• Stay Connected – Receive a phone allowance to keep you plugged in.
• Bring Your Best Friend – Our offices are pet-friendly!

Salary range

$160,000 to $185,000 annually, plus bonus based on KPIs

Work Schedule:

Monday to Friday, 8:30 a.m. to 5 p.m.

Permanent, full-time, hybrid or remote

Location:

Montreal (QC) , Kitchener (ON) or Vancouver (BC)

Application Deadline  

June 30, 2026

Ce poste est également affiché en français. 

Quadbridge is an equal opportunity employer, committed to diversity and inclusion in compliance with the Canadian Human Rights Act and Employment Equity Act. If you require accommodations under the Accessibility for Ontarians with Disabilities Act (AODA) and other applicable Canadian laws during the interview process, please inform us, and we will ensure your needs are met.

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Strong extended health benefits: Health & Prescription coverage, vision and dental care, virtual health care, out-of-country medical coverage
• Insurance coverage (life, short-term disability, long-term disability, and more)
• Health Care Spending Account
• Two different Employee Assistance Programs
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

Note: Benefits may vary by location and are subject to local regulations.

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Vancouver_Canada

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As a Fullstack software engineer, you will work with your team and product management to make insights from data simple. We are looking for engineers that are customer obsessed, who can take on the full scope of the product and user experience beyond the technical implementation. You'll set the foundation for how we build robust, scalable and delightful products.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• 5+ years of experience with HTML, CSS, and JavaScript.
• Passion for user experience and design and a deep understanding of front-end architecture.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember).
• 5+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go).
• Good knowledge of SQL.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Experience developing large-scale distributed systems.

At Databricks, we’re passionate about enabling data teams to solve the world’s toughest problems — from accelerating medical breakthroughs to building the next generation of intelligent products. We do this by creating the world’s best Data Intelligence Platform, empowering customers to turn massive data into deep, actionable insights.

Founded by engineers and driven by innovation, we’re obsessed with designing intuitive, high-performance user experiences that make complex data exploration simple and approachable.

As a Senior Frontend Engineer focused on Dashboards, you’ll build intuitive and scalable end-to-end experiences that help users create, explore, and share insights from data. You’ll work across the frontend, partnering with designers, product managers, and engineers to develop the next generation of dashboards, interactivity, and analytical workflows within Databricks.

What You’ll Do

• Design and build intuitive, high-performance experiences for creating and editing dashboards, as well as for authoring the data behind them, including SQL datasets, custom calculations, and semantic modeling.
• Partner closely with design and product to translate complex analytical concepts into polished, intuitive, and efficient dashboard experiences.
• Drive innovation in how Databricks users interact with data, enabling seamless and responsive exploration at scale.
• Own frontend development for core dashboard workflows, with a focus on usability, performance, accessibility, and reliability.
• Help shape the architecture, abstractions, and platform foundations that support a broad range of dashboarding and analytical use cases.
• Collaborate with backend engineers and adjacent teams to define APIs, data models, and contracts that power interactive and scalable dashboard experiences.

What We Look For

• 5+ years of professional software engineering experience, with strong experience building both frontend and backend systems.
• Expertise in modern frontend development with HTML, CSS, JavaScript/TypeScript, and React, or similar frameworks.
• Deep understanding of UX principles, accessibility, and responsive design for data-heavy interfaces.
• Experience designing scalable systems and abstractions that support interactive, high-performance product experiences.
• Proven ability to collaborate cross-functionally and deliver impactful user-facing features.
• Experience building dashboards, analytics, data exploration, authoring tools, or business intelligence products is a plus.
• Familiarity with SQL authoring, custom calculations, semantic modeling, or related analytical workflows is a plus.
• Experience with cloud technologies such as AWS, Azure, GCP, or Kubernetes is preferred.

P-1440

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value and impact.
• 5+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience developing large-scale distributed systems.
• Experience working on a SaaS platform or with Service-Oriented Architectures.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Experience with security and systems that handle sensitive data.
• Good knowledge of SQL.

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As a Fullstack software engineer, you will work with your team and product management to make insights from data simple. We are looking for engineers that are customer obsessed, who can take on the full scope of the product and user experience beyond the technical implementation. You'll set the foundation for how we build robust, scalable and delightful products.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• 10+ years of experience with HTML, CSS, and JavaScript.
• Passion for user experience and design and a deep understanding of front-end architecture.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember).
• 10+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go).
• Good knowledge of SQL.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Experience developing large-scale distributed systems.

RDQ226R533

At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

We are the “AI/BI” team responsible for making Databricks the best product for business users to create, find and consume data insights. We work on 4 key pillars Dashboards, Genie, Databricks One and Unity Catalog Business semantics. UC Business semantics allow users to define business metrics and agent metadata in centrally governed systems for trusted access. Databricks One offers users a simplified experience tailored for non technical users to find and consume data insights. Genie lets users talk to their data with state of the art text-to-SQL and Dashboards lets users run their day to day business.

We're seeking a dedicated Engineering Leader who will help grow the Data visualization and UC Business Semantics teams.These teams will be tackling a number of challenging fullstack problem spaces, including: making visualizations easy to consume, enabling dashboards to be highly interactive, creating compelling augmented analytics experiences, providing best in class low/no code authoring, and increasing the analytical expressivity of our business semantics products.

You will report directly to the Senior Manager of Engineering.

The main responsibilities include:

• You will lead a talented engineering team of full stack engineers and SMEs focused on one of the above initiatives.
• You will oversee sustained recruitment of top-tier talent, and developing talent on the team.
• You will build processes to implement product vision and strategy, according to organizational goals and priorities.
• You will build software that is not just high quality, but easy to operate.
• You will manage technical debt, including long-term technical architecture decisions, and balance product roadmap.

What we look for:

• Great at hiring and developing talent
• Great at creating efficient processes that increase velocity and quality
• 2+ years of experience in managing teams that build and operate systems in a SaaS environment
• 5+ years of experience with distributed systems and building platforms and services and best in class application experience which serve multiple product teams and customers
• Have experience in scaling engineering teams from 5 to 20+
• Team player that will work with other departments (PM, CS) and engineering teams.
• BS or higher in Computer Science, or a related field
• Strong track record of attracting, hiring, and retaining top engineering talent
• Experience managing distributed teams across multiple locations.
• Adaptability and resilience in a fast-paced, rapidly evolving tech environment

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value and impact.
• 10+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience developing large-scale distributed systems.
• Experience working on a SaaS platform or with Service-Oriented Architectures.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Experience with security and systems that handle sensitive data.
• Good knowledge of SQL.

P-1381

At Databricks, we are passionate about enabling Data & AI teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for data interaction to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

About the Team:

The Backline Engineering Team serves as the critical bridge between Frontline Support and Engineering. We handle complex technical issues and escalations across the Data and AI ecosystem. With a strong focus on customer success, we are committed to delivering exceptional customer satisfaction by providing deep technical expertise, proactive issue resolution, and continuous platform improvements. We emphasise automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform and the health of our products. By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a delightful experience for both customers and internal teams.

What your impact will be:

• Deep Dive Troubleshooting: Conduct deep-dive forensics into Spark core internals and the broader Databricks Data and AI ecosystem to resolve high-priority architectural failures and complex system anomalies.
• Root Cause Analysis: Perform advanced code-level analysis and resource profiling to identify and mitigate systemic root causes, ensuring the stability and reliability of high-scale production workloads.
• Architectural Optimization: Optimise architectural performance across the Data and AI stack by refining execution parameters and enforcing best practice strategies to maximise resource efficiency and throughput.
• Product Improvements: Analyse global issue trends and patterns to partner directly with Product Engineering, influencing the product roadmap and driving initiatives that enhance long-term supportability.
  Scalability & Tooling: Develop reproduction frameworks, automated workflows, and AI-driven diagnostic tools that translate complex backline findings into standardised resolution paths to empower and scale the broader organisation.

What we look for:

We are looking for customer-obsessed candidates with 10+ years of relevant experience, including deep expertise in one of the following three specialized tracks, along with proven experience in managing both customers and technical stakeholders. Since each track calls for a different set of technical capabilities, we’re looking for excellence in one area rather than proficiency in all: 

• Data Engineering Track: Expertise in large-scale big data solutions and ETL pipelines using Spark, Delta Lake, or Hive. Strong experience troubleshooting failures, diagnosing performance issues, and identifying root causes. Demonstrated problem-solving ability and understanding of data engineering best practices to ensure reliable, efficient workflows. Solid hands-on programming skills in Python, SQL, or Scala.
• Product Supportability Track: Deep understanding of distributed system internals. Ability to perform code-level root-cause analysis and profiling (using metrics and heap/thread dumps) in Java, Scala, or Python. Proven record of contributing to bug fixes and mentoring other engineers.
• AI Track: Experience with large-scale machine learning and generative AI systems, including LLM-based applications and agent-driven workflows. Strong grasp of model training, evaluation, and deployment in distributed environments. Experience managing the ML lifecycle, including governance and operationalisation. Skilled in diagnosing and optimising distributed ML workloads for performance and scalability.