BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

MaintainX is the world’s leading mobile-first Asset and Work Intelligence platform for industrial and frontline environments. We’re a modern, IoT-enabled, cloud-based solution that powers maintenance, safety, and operations on physical equipment and facilities.

We help 12,000+ organizations—including Duracell, Univar Solutions, Titan America, McDonald’s, Brenntag, Cintas, Xylem, and Shell—achieve operational excellence and reliability at scale.

Following our $150 million Series D led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, valuing the company at $2.5 billion.

As we enter our next phase of growth, we’re investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate—predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure.

The Role

We are seeking a highly skilled and motivated Senior Applied Machine Learning Developer to guide the technical direction and architecture of our Predictive Maintenance and Asset Intelligence initiatives.

You’ll combine deep ML expertise with strong software development and leadership skills—mentoring developers, scaling systems, and driving the roadmap for AI-enabled maintenance intelligence across thousands of industrial sites.

This role sits at the intersection of ML architecture, IoT data systems, and product impact, shaping the foundation for MaintainX’s predictive and generative AI strategy.

What you’ll do:

• Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products.
• Architect end-to-end ML systems—from data ingestion and feature development to model training, deployment, and monitoring.
• Mentor a growing team of ML and data developers, instilling best practices for experimentation, evaluation, and model lifecycle management.
• Partner with product and software development leaders to align AI roadmap with customer needs and business goals.
• Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining.
• Drive performance optimization through techniques like quantization, distillation, and scalable inference serving.
• Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence.
• Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security.

About you:

• 7+ years of experience in Machine Learning, Data Science, or Applied AI.
• Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar).
• Proven experience deploying production ML systems—not just prototypes—at scale.
• Strong background in LLMs, time-series modeling, and anomaly detection for real-world data.
• Demonstrated ability to lead architectural decisions, mentor developers, and collaborate across product, data, and platform teams.
• Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred.

Bonus skills: 

• Experience with OCR for extracting structured data from documents.
• Background in time-series modeling for predictive maintenance and anomaly detection.
• Familiarity with Industrial IoT systems (sensors, telemetry, edge computing).
• Experience applying reinforcement learning or agentic architectures for decision-making and control systems.
• Contributions to open-source ML frameworks or research in reliability, explainability, or digital twins.

What’s in it for you:

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrollment program.
• Take what you need PTO.
• A high impact Culture:
• You’ll work with Smart, Humble Optimists across the globe.
• Meritocratic environment where ideas and outcomes are publicly celebrated.

About us:

We exist to make the lives of frontline and maintenance teams easier by building software that meets their real-world needs. Our product transforms how 80% of the global workforce—those who don’t sit behind a desk—manage their operations, assets, and teams.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

MaintainX est la première plateforme mobile au monde dédiée à la gestion des actifs et des tâches dans les environnements industriels et de première ligne. Nous proposons une solution moderne, basée sur l'IoT et le cloud, qui facilite la maintenance, la sécurité et l'exploitation des équipements et installations physiques.

Nous aidons plus de 12 000 organisations, dont Duracell, Univar Solutions, Titan America, McDonald's, Brenntag, Cintas, Xylem et Shell, à atteindre l'excellence opérationnelle et la fiabilité à grande échelle.

À la suite de notre série D de 150 millions de dollars menée par Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures et Ridge Ventures, MaintainX a levé un total de 254 millions de dollars, valorisant la société à 2,5 milliards de dollars.

Alors que nous entrons dans notre prochaine phase de croissance, nous investissons massivement dans l'IA/ML, les LLM et l'IoT industriel afin de transformer le mode de fonctionnement des équipes de première ligne, en prédisant les pannes avant qu'elles ne se produisent, en automatisant les flux de travail et en intégrant l'intelligence dans chaque actif et chaque procédure.

Le poste

Nous recherchons un développeur(se) senior en apprentissage automatique appliqué hautement qualifié et motivé pour orienter la direction technique et l'architecture de nos initiatives en matière de maintenance prédictive et d'intelligence des actifs.

Vous combinerez une expertise approfondie en apprentissage automatique avec de solides compétences en génie logiciel et en sens du leadership. Vous encadrerez des ingénieurs, développerez des systèmes et piloterez la feuille de route pour l'intelligence de maintenance basée sur l'IA sur des milliers de sites industriels.

Ce poste se situe à la croisée de l'architecture d'apprentissage automatique, des systèmes de données IoT et de l'impact des produits, et constitue le fondement de la stratégie d'IA prédictive et générative de MaintainX.

Ce que vous ferez:

• Diriger la direction technique pour la maintenance prédictive, la détection des anomalies et l'intelligence alimentée par LLM dans tous les produits MaintainX.
• Concevoir des systèmes ML de bout en bout, de l'ingestion des données et le développement des fonctionnalités à la formation, au déploiement et à la surveillance des modèles.
• Encadrer une équipe croissante de développeurs(ses) ML et de données, en inculquant les meilleures pratiques en matière d'expérimentation, d'évaluation et de gestion du cycle de vie des modèles.
• Collaborer avec les responsables des produits et de développement afin d'aligner la feuille de route de l'IA sur les besoins des clients et les objectifs commerciaux.
• Concevoir des boucles de données et de rétroaction fiables qui relient la télémétrie des clients et les commentaires des opérateurs au réentraînement des modèles.
• Optimiser les performances grâce à des techniques telles que la quantification, la distillation et le service d'inférence évolutif.
• Travailler avec des cadriciels LLM (LangChain, LlamaIndex, Hugging Face) pour créer des systèmes de raisonnement et des flux de travail agentifs pour l'intelligence des actifs et du travail.
• S'assurer que l'infrastructure ML répond aux normes de production en matière de latence, de fiabilité, d'explicabilité et de sécurité.

À propos de vous:

• Plus de 7 ans d'expérience dans le domaine de l'apprentissage automatique, de la science des données ou de l'IA appliquée.
• Expertise en Python et excellente maîtrise de PyTorch, TensorFlow et des piles ML cloud (AWS, Databricks ou similaires).
• Expérience avérée dans le déploiement à grande échelle de systèmes ML de production, et pas seulement de prototypes.
• Solide expérience en LLM, modélisation de séries chronologiques et détection d'anomalies pour les données du monde réel.
• Capacité avérée à diriger les décisions architecturales, à encadrer les développeurs(ses) et à collaborer avec les équipes chargées des produits, des données et des plateformes.
• Connaissance des outils MLOps (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
• Diplôme de deuxième cycle (master/doctorat) en informatique, apprentissage automatique ou dans un domaine connexe préféré.

Une attention particulière est accordée aux candidats présentant les caractéristiques suivantes:

• Expérience avec l'OCR pour l'extraction de données structurées à partir de documents.
• Expérience dans la modélisation de séries chronologiques pour la maintenance prédictive et la détection d'anomalies.
• Connaissance des systèmes IoT industriels (capteurs, télémétrie, edge computing).
• Expérience dans l'application de l'apprentissage par renforcement ou des architectures agentuelles pour les systèmes de prise de décision et de contrôle.
• Contributions à des frameworks ML open source ou à la recherche dans les domaines de la fiabilité, de l'explicabilité ou des jumeaux numériques.

Quels sont les avantages pour vous?:

• Un salaire compétitif et des opportunités d'équité significatives.
• Couverture des soins de santé, des soins dentaires et de la vue.
• Programme d'inscription 401(k) / RRSP.
• Prenez les congés dont vous avez besoin.
• Une culture du travail :
• Vous travaillerez avec des personnes intelligentes, humbles et optimistes à travers le monde.
• Un environnement méritocratique où les idées et les résultats sont publiquement célébrés.

Qui sommes-nous:

MaintainX s'engage à créer un environnement diversifié. Tous les candidats qualifiés seront pris en considération pour un emploi sans considération de race, de couleur, de religion, de sexe, d'identité ou d'expression de genre, d'orientation sexuelle, d'origine nationale, de génétique, d'invalidité, d'âge ou de statut d'ancien combattant.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Rumble Cloud is seeking a Principal Software Architect (Python) to own the design and hands-on implementation of our Self-Service Cloud Portal and Cloud Console, the primary interfaces customers use to manage their cloud environments. Our stack is built on OpenStack and Ceph, with a customer surface that includes a self-service portal, an enhanced open-source cloud console, and integrated CRM/ERP-based billing and account management.

This role combines architectural leadership with significant day-to-day coding. You will define the architectural roadmap, guide the team in building scalable, maintainable services, and personally deliver high-quality Python code. Partnering with backend, Golang, and React/TypeScript teams, you will ensure cohesive design, strong performance, and an excellent developer and customer experience, while helping prioritize work and mentoring engineers without direct people management responsibilities.

Key Responsibilities
Architecture and Technical Vision

• Define, document, and communicate architectural patterns, standards, and best practices for backend services, microservice integration, and portal-wide interoperability.
• Evaluate the current codebase (including CRM/billing integration and cloud console frontend) and chart a practical path toward a scalable, maintainable architecture.
• Design architectures that support multi-tenant SaaS scale, observability, reliability, and future extensibility.
• Maintain architecture diagrams, service specifications, and operational design records for cross-functional transparency.
• Collaborate with platform and infrastructure teams to align service design with Rumble Cloud OpenStack/Kubernetes-based runtime environment.

Hands-On Development
• Contribute clean, efficient Python code (e.g., FastAPI, SQLAlchemy, Jinja2) for key backend components; this role requires sustained coding, not occasional guidance.
• Build and extend backend functionality that interfaces with RESTful APIs and SQL databases.
• Partner with Golang service teams and frontend developers (React/TypeScript) for seamless integration across the product ecosystem.
• Analyze product requirements and implement new features end-to-end, proactively identifying and addressing potential issues.

Planning, Prioritization, and Delivery
• Translate product-level requirements and customer needs into actionable roadmaps, epics, and tickets.
• Help prioritize features and technical debt based on impact, dependencies, and realistic timelines.
• Drive continuous improvement in the delivery lifecycle, including code review practices, release automation, and GitHub/GitHub Actions workflows.
• Help design and implement an SDLC and SSDLC with repeatable processes for planning, development, testing, deployment, and security review.
• Identify risks and blockers early and work with stakeholders to resolve them before they affect delivery.

Mentorship and Team Guidance
• Guide senior and mid-level engineers through design reviews, pair programming, and technical planning.
• Document designs and mentor engineers to grow their architectural thinking and engineering skills.
• Communicate technical decisions and trade-offs clearly to both engineering and non-technical stakeholders.
• Collaborate with other teams and departments on integrating new functionalities and services.

Qualifications
Required Qualifications
• Expert-level Python development experience, including SQLAlchemy, Jinja2, and modern API frameworks (e.g., FastAPI, Flask, Gunicorn).
• Strong experience designing and implementing RESTful APIs and resource servers, including working with incomplete or minimal SDK documentation.
• Experience designing and implementing authentication and authorization mechanisms such as OAuth2 and OpenID Connect.
• Strong understanding of relational databases (PostgreSQL, MySQL), ORM patterns, and schema design.
• Demonstrated experience architecting distributed systems or service-oriented architectures at production scale.
• Proficiency with object-oriented and functional programming concepts.
• Proficiency with containerized development (Docker) and cloud-native deployment environments (Kubernetes).
• Hands-on familiarity with Git-based workflows, including GitHub, pull requests, and CI/CD pipelines.
• Ability to synthesize product-level requirements into actionable technical roadmaps and system designs.
• Excellent communication and mentoring skills, with a track record of guiding engineering teams toward delivery excellence.
• Demonstrated ability to act as a hands-on technical leader while maintaining architectural oversight across multiple services and teams.
• Strong problem-solving and debugging skills across complex, distributed systems.
• Ability to work effectively in a fast-paced environment, balancing immediate delivery needs with long-term architectural goals.
• Willingness to learn, be challenged, and contribute in a dynamic, fast-paced environment, with a passion for cloud-native development and open-source tooling.

Preferred Qualifications
• Strong Go (Golang) programming experience, with the ability to contribute to and review Go-based services.
• Familiarity with OpenStack APIs, services, or the broader OpenStack ecosystem.
• Familiarity with Ceph or other distributed storage systems.
• Experience with the Odoo ERP/CRM platform, including module development, customization, or integration into SaaS products.
• Background working with or extending open-source cloud console or dashboard projects.
• General familiarity with public cloud concepts (e.g., AWS, Google Cloud, Microsoft Azure).
• Experience building SaaS in a multi-tenant environment, including tenant isolation, usage metering, and self-service provisioning.
• Experience with OpenStack or Kubernetes API development, control panel design/architecture, and test-driven development with Pytest.
• Experience working within public cloud / IaaS products
• Intermediate experience or higher in 1 or more programming languages (ie: Go, C, C++, Python, Rust)
• Experience working with Rocky or Ubuntu in live environments.
• Experience working with MySQL and/or PostgreSQL 

Annual Compensation Range: 

$150,000 - $186,000 CAD base + benefits + equity (If based in Canada)

$160,000 - $195,000 USD base + benefits + equity (If based in the United States)

Note: The salary range listed for this position is a good faith estimate based on experience, qualifications, and internal compensation structure. The actual salary offered varies depending on the candidate's skill level and experience.

This posting refers to an active vacancy within the organization.

About the Role:

Rumble Cloud is seeking a Kubernetes Engineer to support our team in rolling out and operating our next-generation Kubernetes platform. This role will focus on our new CAPI/CAPO-based Kubernetes solution, which is designed to be compatible with our existing OpenStack Magnum API and will be deployed across our public cloud. You will help run the day-to-day operations of the Kubernetes service, assist with migrations and onboarding from our current Magnum-based offering, and act as an escalation point for complex customer issues that go beyond front-line support. This is a hands-on engineering role for someone who enjoys debugging difficult problems, improving reliability, and working closely with both platform engineers and customer-facing teams.

Key Responsibilities:

• Operate and maintain Rumble Cloud’s Kubernetes platform, including our new CAPI/CAPO-based installation and its integration with the OpenStack Magnum API.
• Assist in the rollout, migration, and upgrade processes as customers transition from the existing Magnum-based solution to the new platform.
• Serve as an escalation point for customer support, troubleshooting complex Kubernetes and cluster lifecycle issues.
• Monitor the health, performance, and capacity of Kubernetes clusters and underlying infrastructure; assist in incident response and root cause analysis.
• Implement and maintain day-2 operations processes, including backup/restore, scaling, patching, and cluster upgrades.
• Collaborate with the Kubernetes Architect to implement standards, best practices, and reference patterns for cluster configuration and operations.
• Help manage and integrate container registries, identity, networking, and storage components required for the Kubernetes platform.
• Automate repetitive operational tasks using scripting and infrastructure-as-code tools.
• Contribute to and maintain runbooks, documentation, and knowledge base articles for both internal teams and customer-facing support.
• Provide feedback from operations and customer interactions to influence platform improvements and product roadmap.

Required Skills & Experience:

• Extensive experience in Linux systems engineering, cloud engineering, or platform/SRE roles, including hands-on work with Kubernetes in production environments.
• Practical experience with installing, operating, and troubleshooting Kubernetes in production environments.
• Experience working with Kubernetes on OpenStack or other cloud providers.
• Familiarity with Cluster API (CAPI) and/or Cluster API Provider OpenStack (CAPO), or strong willingness to ramp up quickly.
• Strong understanding of Linux, containers, and container runtimes (e.g., Docker, containerd).
• Experience with Kubernetes networking, storage, and ingress concepts (CNI, CSI, load balancers, ingress controllers).
• Hands-on experience with scripting and automation (e.g., Bash, Python, or Go) for operational tasks.
• Familiarity with configuration management and IaC tools such as Ansible and Terraform.
• Experience with monitoring and logging in Kubernetes environments (e.g., Prometheus, Grafana, ELK/Graylog, or similar).
• Strong troubleshooting skills, clear written documentation, and effective communication with both technical and non-technical stakeholders.

Nice to Have (Preferred Skills):

• Experience with OpenStack Magnum and its Kubernetes integrations.
• Experience operating Kubernetes on other public cloud platforms (EKS, AKS, GKE).
• Knowledge of Ceph, S3-compatible storage, and their use with Kubernetes.
• Understanding of application architectures on Kubernetes, including microservices and 12-factor applications.
• Exposure to CI/CD toolchains (e.g., Git, GitLab/Jenkins, Artifactory, etc.) for containerized workloads.
• Experience with security hardening and best practices for Kubernetes (RBAC, PodSecurity, network policies, image scanning).

Qualifications:

• Demonstrated experience operating production Kubernetes clusters and working as part of a cross-functional cloud/platform team.
• Ability to work effectively under pressure, handle escalations, and maintain a strong customer-focused mindset.
• Passion for continuous learning in Kubernetes, cloud-native tooling, and automation.

Annual Compensation Range: 

Note: The salary range listed for this position is a good faith estimate based on experience, qualifications, and internal compensation structure. The actual salary offered varies depending on the candidate's skill level and experience. This posting refers to an active vacancy within the organization.

We are seeking a Data Engineer to join our dynamic team. The ideal candidate is an enthusiastic problem-solver who excels at building scalable data systems and has hands-on experience with Databricks, Looker, AWS, MongoDB, PostgreSQL, and Terraform. You will work alongside sales, customer success and engineering to design, implement, and maintain the operational data infrastructure that powers our analytics and platform offerings.

What you'll do:

1. Data Pipeline & Integration
• Design, build, and maintain end-to-end data pipelines using Databricks (SparkSQL, PySpark) for data ingestion, transformation, and processing.
• Integrate data from various structured and unstructured sources, including medical imaging systems, EMRs, Change-Data-Capture from SQL Databases, and external APIs.
2. Analytics & Visualization
• Collaborate with the analytics team to create, optimize, and maintain dashboards in Looker.
• Implement best practices in data modeling and visualization for operational efficiency.
3. Cloud Infrastructure
• Deploy and manage cloud-based solutions on AWS (e.g., S3, EMR, Lambda, EC2) to ensure scalability, availability, and cost-efficiency using IaC tooling (Terraform and Databricks Asset Bundles).
• Develop and maintain CI/CD pipelines for data-related services and applications.
4. Database Management
• Oversee MongoDB and PostgreSQL databases, including schema design, indexing, and performance tuning.
• Ensure data integrity, availability, and optimized querying for both transactional and analytical workloads.
5. Security & Compliance
• Adhere to healthcare compliance requirements (e.g., HIPAA) and best practices for data privacy and security.
• Implement error handling, logging, and monitoring frameworks to ensure reliability and transparency.
• Implement data governance frameworks to maintain data integrity and confidentiality.
6. Collaboration & Documentation
• Work cross-functionally with data scientists, product managers, and other engineering teams to gather requirements and define data workflows.
• Document data pipelines, system architecture, and processes for internal and external stakeholders.

About you:

• Education & Experience
• 7+ years of professional experience in data engineering or a similar role.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Technical Skills
• Databricks (Spark): Proven expertise in building large-scale data pipelines.
• Looker: Experience in creating dashboards, data models, and self-service analytics solutions.
• AWS: Proficient with core services like S3, EMR, Lambda, IAM, EC2, etc.
• MongoDB & PostgreSQL: Demonstrated ability to design schemas, optimize queries, and manage high-volume databases.
• SQL & Scripting: Strong SQL skills, plus familiarity with Python, Scala, or Java for data-related tasks.
• Soft Skills
• Excellent communication and team collaboration abilities.
• Strong problem-solving aptitude and analytical thinking.
• Detail-oriented, with a focus on delivering reliable, high-quality solutions.
• Preferred
• Experience in healthcare or imaging (e.g., DICOM, HL7/FHIR).
• Familiarity with DevOps tools (Docker, Kubernetes, Terraform) and CI/CD pipelines.
• Knowledge of machine learning workflows and MLOps practices.

The base salary range for this position is $120,000 - $180,000.  Our job postings cover multiple career levels and individual compensation will depend on various factors, including qualifications, skills, experience, location, and applicable laws. In addition to base salary, this role is eligible to participate in our equity incentive and competitive benefits plans.