About the Role

We’re looking for a Data Science Engineer with 7+ years of experience to join the Revenue Intelligence team at Veeam. This role is ideal for someone who thrives in a fast-paced environment, enjoys building scalable data solutions, and is passionate about driving business impact through analytics, machine learning, and AI. You’ll work closely with cross-functional teams to turn data into actionable insights and intelligent applications.

What You’ll Do

• Design and implement data science, machine learning, and AI solutions to support strategic decision-making
• Perform deep-dive quantitative and qualitative analyses to validate business hypotheses and drive improvements
• Contribute to cross-functional initiatives involving data science, ML, and AI engineering use cases
• Develop knowledge bases from structured and unstructured data to support RAG systems and AI agents
• Build data-driven applications (e.g., Streamlit) to enable internal access to AI-powered capabilities
• Partner with stakeholders to deliver actionable insights and recommendations
• Continuously improve processes and identify opportunities for automation and efficiency

Technologies You’ll Work With

Python, SQL, Machine Learning & AI Frameworks, Databricks / PySpark, Data Visualization Tools (Streamlit, Tableau, Power BI, Qlik)

What You’ll Bring

• 7+ years of professional experience in data science, analytics, or machine learning roles
• Strong proficiency in Python and SQL
• Experience building scalable data science solutions (feature engineering, model training, evaluation, deployment, MLOps)
• English Bilingual
• Solid understanding of data engineering concepts (ETL/ELT, data modeling, pipelines, governance)
• Experience integrating LLMs into production systems (prompt engineering, RAG, AI agents)

Bonus Skills

• Experience with software engineering best practices (APIs, testing, version control, deployment)
• Hands-on experience with Databricks or PySpark
• Familiarity with data visualization platforms and storytelling with data
• Experience using project management and collaboration tools (Jira, Trello, Confluence)
• Strong technical writing and documentation skills

What You’ll Get

• Two weeks of paid vacation, 12 statutory holidays, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
• Paid parental leave: 8 days for fathers, 122 days for birthing parents, 92 days for adoptive parents
• Medical, dental, and vision coverage fully funded through INS Premium for employees and dependents
• Mental health support, therapy sessions, and virtual care via our Employee Assistance Program
• Retirement and social security contributions through Costa Rica’s statutory programs
• Life insurance equal to 24x monthly salary, plus disability and funeral coverage
• Daily cafeteria subsidy
• Fertility, adoption, and surrogacy support, plus 24 paid volunteer hours through Veeam Cares
• Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning

#LI-CC1

Linqia is the leader in the influencer marketing industry. We’re a growing tech start-up, having experienced 100% year-over-year growth and break-even. At Linqia, we partner with the world’s largest brands including Danone, AB InBev, Kimberly-Clark, Unilever, and Walmart to build compelling and effective influencer marketing campaigns. Our AI-driven platform and team of experts are leading the transformation of influencer marketing.

We value intelligence, recognize talent and have instilled a culture that supports career development and growth for our employees. We thrive on innovation and accountability, with a customer first attitude that adds true value to everything we touch. Our team members are smart, hard-working, have integrity and love to have fun as we play to win.

SOFTWARE AND INFRASTRUCTURE DEVOPS ENGINEER

Experience level  3+ YoE supporting production saas in AWS 

Location Anywhere in LATAM preferably in Colombia

Employment type Full‑time contract

ABOUT THE ROLE

Build out  a cloud‑native team that owns the entire software delivery life cycle on Amazon Web Services. You will combine deep Kubernetes expertise with Python and shell scripting to automate, monitor, and continuously improve the Linqia platform while driving FinOps practices to keep our cloud footprint efficient. Work in a GitOps culture where every change is delivered through pull requests and rolled out by automated pipelines.

WHAT YOU WILL DO

• Design, maintain, and evolve our AWS account structure, VPC networking, IAM policies, security boundaries, and cost‑management controls using Terraform and the AWS console
• Maintain secure networking layers with AWS load balancers, ingress controllers, service‑mesh policies, network policies, and zero‑trust principles
• Operate and harden production‑grade Kubernetes clusters on AWS EKS, including upgrades, service mesh, policy management, and multi‑cluster architectures driven by Argo CD
• Build reusable infrastructure‑as‑code modules with Terraform that provision cloud resources in minutes while enforcing tagging standards and least‑privilege access
• Create self‑service CI/CD pipelines in Jenkins and GitHub Actions for fast, safe releases with automated testing and promotion across environments
• Deliver real‑time observability with Datadog, Prometheus, Grafana, CloudWatch, and OpenTelemetry, and use these tools to assist in solving production bugs and issues
• Administer and maintain purpose-built Linux VMs via configuration management tools like Puppet, Ansible, or Chef
• Deploy, scale, and maintain databases on AWS (Aurora, PostgreSQL, MySQL, OpenSearch, etc.), maintaining high database performance/uptime, optimizing tables and datasets, and ensuring disaster recovery protocols are in place.  
• Support developers by maintaining Podman‑based local dev boxes and Kubernetes staging environments that mirror production, ensuring smooth hand‑off from local code to cloud‑native deployments
• Implement FinOps practices: track and forecast AWS spend, enforce cost‑allocation tagging, identify rightsizing opportunities, manage Savings Plans or Reserved Instances, and build cost‑optimisation dashboards for engineering and finance stakeholders
• Write automation utilities and command‑line tools in Python and craft shell scripts that glue components and workflows together
• Champion reliability through incident reviews, capacity planning, game days, chaos testing, and service‑level objective tracking
• Collaborate in Agile rituals, plan sprints, refine backlog tickets, and pair with peers to spread DevOps and FinOps best practices

WHAT YOU BRING

• Bachelor degree in Computer Science or equivalent practical experience
• three plus years working with cloud infrastructure or platform engineering focused on AWS
• Deep hands‑on experience with Kubernetes, preferably EKS, covering upgrades, networking, storage, RBAC, and custom resources
• Proficiency in Python and Bash or Zsh scripting
• Strong understanding of core AWS services EC2, VPC, IAM, ALB, S3, RDS, CloudFormation, and CloudWatch
• Demonstrated experience applying FinOps principles: cost monitoring, forecasting, and optimisation on AWS
• Solid experience with Docker and container runtimes, with emphasis on Podman for local development environments
• Hands‑on practice with configuration‑management tools such as Ansible or Puppet and infrastructure‑as‑code with Terraform
• Proven use of Datadog for metrics, logs, and APM, plus familiarity with Prometheus and Grafana dashboards
• Comfortable with Git‑based workflows, feature branching, and pull‑request reviews
• Strong SQL skills and a deep understanding of relational database internals
• Competent in Linux administration, process troubleshooting, and performance tuning
• Practical knowledge of TCP/IP, HTTP, TLS, DNS, and common networking tools
• Clear communication skills and an ability to translate complex technical topics to diverse audiences
• Familiarity with Scrum or Kanban and a continuous‑improvement mindset

EXTRA CREDIT

• AWS certifications such as Solutions Architect, DevOps Engineer, or FinOps Practitioner
• Experience with AWS security tooling GuardDuty, Security Hub, IAM Access Analyzer, and KMS
• Building data pipelines with Apache Spark, Flink, or similar frameworks
• Implementing event‑driven architectures with Kafka Streams or KSQL
• Applying SRE practices such as error budgets and service‑level dashboards
• Exposure to machine‑learning workflows, ModelOps, or MLOps in production

_{This position description is intended to describe the duties most frequently performed by an individual in this position. Linqia is an equal opportunity employer supporting workforce diversity. We actively encourage women, people with disabilities, veterans, underrepresented minorities, and LGBTQ+ people to apply. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, or disability status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.}

_{Headhunters and recruitment agencies may not submit resumes or candidates through this Web site or directly to employees. Linqia does not accept unsolicited headhunter and agency resumes and will not pay fees to any third-party agency or company that does not have a signed agreement with us.}

Important Information 

Location: Costa Rica

Work Mode: Hybrid

Job Summary 

As a Senior Machine Learning Engineer (20529), you will be responsible for designing, developing, and maintaining high-quality software solutions. You will collaborate with cross-functional teams to understand business requirements and translate them into scalable and efficient software applications. Your role will involve leading technical projects, mentoring junior engineers, and continuously improving software development practices to ensure the delivery of robust and reliable software systems.  

Responsibilities and Duties 

• Design, build, and deploy scalable machine learning models and pipelines across the full ML lifecycle
• Develop and optimize data processing workflows using Python, SQL, and distributed frameworks such as PySpark
• Deploy and monitor machine learning models in cloud environments, ensuring performance, reliability, and scalability
• Collaborate with cross-functional teams to translate business problems into data-driven solutions and improve model performance

Qualifications and Skills 

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent practical experience
• 5+ years of experience as a Machine Learning Engineer with a focus on deploying and scaling ML systems
• Strong proficiency in Python, SQL, and PySpark for large-scale data processing
• Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or XGBoost
• Experience designing and managing end-to-end ML pipelines using tools such as MLflow or similar
• Experience deploying models in cloud platforms such as AWS, GCP, Azure, or Databricks
• Strong understanding of MLOps practices including CI/CD, model versioning, and automated retraining
• Experience working with containerized environments and Kubernetes for ML workloads
• Ability to design evaluation metrics and validate model performance effectively
• Strong communication and collaboration skills to work with cross-functional teams and stakeholders

About Encora 
 
Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others.  

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.  

Linqia is the leader in the influencer marketing industry. We’re a growing tech start-up, having experienced 100% year-over-year growth and break-even. At Linqia, we partner with the world’s largest brands including Danone, AB InBev, Kimberly-Clark, Unilever, and Walmart to build compelling and effective influencer marketing campaigns. Our AI-driven platform and team of experts are leading the transformation of influencer marketing.

We value intelligence, recognize talent and have instilled a culture that supports career development and growth for our employees. We thrive on innovation and accountability, with a customer first attitude that adds true value to everything we touch. Our team members are smart, hard-working, have integrity and love to have fun as we play to win.

SOFTWARE AND INFRASTRUCTURE DEVOPS ENGINEER

Experience level  3+ YoE supporting production saas in AWS 

Location Anywhere in LATAM preferably in Colombia

Employment type Full‑time contract

ABOUT THE ROLE

Build out  a cloud‑native team that owns the entire software delivery life cycle on Amazon Web Services. You will combine deep Kubernetes expertise with Python and shell scripting to automate, monitor, and continuously improve the Linqia platform while driving FinOps practices to keep our cloud footprint efficient. Work in a GitOps culture where every change is delivered through pull requests and rolled out by automated pipelines.

WHAT YOU WILL DO

• Design, maintain, and evolve our AWS account structure, VPC networking, IAM policies, security boundaries, and cost‑management controls using Terraform and the AWS console
• Maintain secure networking layers with AWS load balancers, ingress controllers, service‑mesh policies, network policies, and zero‑trust principles
• Operate and harden production‑grade Kubernetes clusters on AWS EKS, including upgrades, service mesh, policy management, and multi‑cluster architectures driven by Argo CD
• Build reusable infrastructure‑as‑code modules with Terraform that provision cloud resources in minutes while enforcing tagging standards and least‑privilege access
• Create self‑service CI/CD pipelines in Jenkins and GitHub Actions for fast, safe releases with automated testing and promotion across environments
• Deliver real‑time observability with Datadog, Prometheus, Grafana, CloudWatch, and OpenTelemetry, and use these tools to assist in solving production bugs and issues
• Administer and maintain purpose-built Linux VMs via configuration management tools like Puppet, Ansible, or Chef
• Deploy, scale, and maintain databases on AWS (Aurora, PostgreSQL, MySQL, OpenSearch, etc.), maintaining high database performance/uptime, optimizing tables and datasets, and ensuring disaster recovery protocols are in place.  
• Support developers by maintaining Podman‑based local dev boxes and Kubernetes staging environments that mirror production, ensuring smooth hand‑off from local code to cloud‑native deployments
• Implement FinOps practices: track and forecast AWS spend, enforce cost‑allocation tagging, identify rightsizing opportunities, manage Savings Plans or Reserved Instances, and build cost‑optimisation dashboards for engineering and finance stakeholders
• Write automation utilities and command‑line tools in Python and craft shell scripts that glue components and workflows together
• Champion reliability through incident reviews, capacity planning, game days, chaos testing, and service‑level objective tracking
• Collaborate in Agile rituals, plan sprints, refine backlog tickets, and pair with peers to spread DevOps and FinOps best practices

WHAT YOU BRING

• Bachelor degree in Computer Science or equivalent practical experience
• three plus years working with cloud infrastructure or platform engineering focused on AWS
• Deep hands‑on experience with Kubernetes, preferably EKS, covering upgrades, networking, storage, RBAC, and custom resources
• Proficiency in Python and Bash or Zsh scripting
• Strong understanding of core AWS services EC2, VPC, IAM, ALB, S3, RDS, CloudFormation, and CloudWatch
• Demonstrated experience applying FinOps principles: cost monitoring, forecasting, and optimisation on AWS
• Solid experience with Docker and container runtimes, with emphasis on Podman for local development environments
• Hands‑on practice with configuration‑management tools such as Ansible or Puppet and infrastructure‑as‑code with Terraform
• Proven use of Datadog for metrics, logs, and APM, plus familiarity with Prometheus and Grafana dashboards
• Comfortable with Git‑based workflows, feature branching, and pull‑request reviews
• Strong SQL skills and a deep understanding of relational database internals
• Competent in Linux administration, process troubleshooting, and performance tuning
• Practical knowledge of TCP/IP, HTTP, TLS, DNS, and common networking tools
• Clear communication skills and an ability to translate complex technical topics to diverse audiences
• Familiarity with Scrum or Kanban and a continuous‑improvement mindset

EXTRA CREDIT

• AWS certifications such as Solutions Architect, DevOps Engineer, or FinOps Practitioner
• Experience with AWS security tooling GuardDuty, Security Hub, IAM Access Analyzer, and KMS
• Building data pipelines with Apache Spark, Flink, or similar frameworks
• Implementing event‑driven architectures with Kafka Streams or KSQL
• Applying SRE practices such as error budgets and service‑level dashboards
• Exposure to machine‑learning workflows, ModelOps, or MLOps in production

_{This position description is intended to describe the duties most frequently performed by an individual in this position. Linqia is an equal opportunity employer supporting workforce diversity. We actively encourage women, people with disabilities, veterans, underrepresented minorities, and LGBTQ+ people to apply. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, or disability status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.}

_{Headhunters and recruitment agencies may not submit resumes or candidates through this Web site or directly to employees. Linqia does not accept unsolicited headhunter and agency resumes and will not pay fees to any third-party agency or company that does not have a signed agreement with us.}

About the Role

This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results. You will bridge the gap between technical innovation and real-world business challenges by applying advanced statistical and machine learning techniques to build predictive models and derive actionable insights.

What we are looking for

• Experience & Education: Bachelor's degree in Computer Science or Engineering with 8–12 years of relevant experience leading complex technical projects with multi-team impact.
• Advanced ML & Statistics: Expert capability in designing end-to-end ML systems for complex problems (including imbalanced data and concept drift), applying advanced statistical methods (mixed models, survival analysis, Bayesian approaches), and demonstrating a deep understanding of causal inference techniques, experimentation design (A/B testing, MABs), and deep learning architectures for unstructured data (e.g., NLP, Computer Vision).
• Core Technology Stack: Expertise in Python (including libraries like Pandas and NumPy) or R, proficiency with cloud platforms and their data/ML services (e.g., AWS Sagemaker, GCP Vertex AI, Azure ML Services), experience with big data technologies (e.g., Spark, Hadoop), and familiarity with MLOps tools (e.g., Kubeflow, MLflow, Docker).
• Business Immersion: Proven ability to immerse in operations to acquire deep domain expertise, thinking like an insider to translate seamlessly between business needs and engineering solutions.
• Full-Stack Agility: Ability to build complete applications rapidly across any technology stack, selecting the right tools to balance technical debt with delivery speed.
• Data Strategy & Integration: Experience architecting scalable data strategies across diverse teams and complex enterprise landscapes. This includes defining data governance policies, mastering data quality frameworks, building robust integration solutions for undocumented schemas and disparate systems, and driving the adoption of modern data warehousing and lakehouse architectures.
• AI Evaluation & Governance: Experience leading AI governance initiatives, creating evaluation standards, and training teams on rigorous AI verification and risk management.
• Rapid Prototyping: Proficiency in leading rapid delivery initiatives using a prototype-first approach to validate solutions quickly before scaling.
• Problem Discovery: A track record of seeking out undefined problems, embedding with users to discover latent needs, and turning ambiguity into clear problem statements.
  
  

Who you are

• Polymath Oriented: You bridge gaps between engineering, design, business, and science, rapidly immersing yourself in new domains to speak the language of the business.
• Curious Explorer: You seek out ambiguity rather than avoiding it, driving team curiosity through challenging questions and creating an environment that encourages experimentation.
• Outcome Owner: You drive an accountability culture focused on business impact rather than just deliverables, owning relationships and making trade-offs between custom solutions and generalizable work.
• Systems Thinker: You map complex system interactions across technical and business domains, anticipating cascading effects and understanding how technology changes impact operations.
• Precise Communicator: You translate seamlessly between technical and business language, ensuring requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders.
• Problem Discoverer: You embed with users to discover latent needs, turning ambiguity into clear problem statements rather than waiting for defined tasks.

What Appnovation Offers 

• Challenging and rewarding work with real impact
• Direct Access to Cutting-Edge AI Platforms
• Diverse and Inclusive Culture 
• Growth opportunities for personal and professional development
• A collaborative and innovative work environment where your ideas are valued
• Exposure to exciting projects and high-profile clients
• Supportive work environment with access to company leaders
• Hybrid working model

About the Role

Join forces with Appnovation to deliver high-impact results for one of our key strategic partners - a global leader in their field. This engagement offers a unique vantage point into a world-class organization with exceptional opportunities for professional growth and long-term career advancement

As a Senior Data Engineer, you will manage the "discovery-to-scale" pipeline, identifying recurring patterns in the field and handing off validated solutions to Platform Engineers for enterprise generalization. In this forward-deployed role, you will bridge the gap between building technical products and solving real-world business problems through rapid solution delivery and deep domain immersion. Your primary objective is to design and build data integration, storage systems, and infrastructure that enable analytics and AI capabilities.

This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results.

What we are looking for

• Experience & Education: Bachelor's degree in Computer Science or Engineering with 8–12 years of relevant experience leading and delivering complex data engineering projects with multi-team or business impact.
• Enterprise Data Integration & Architecture: Proven expertise in designing, building, and maintaining robust, scalable data pipelines (ETL/ELT). Must demonstrate the ability to navigate complex enterprise data landscapes, effectively handle undocumented schemas, and implement resilient integration solutions for high-volume data.
• Cloud-Native Data Ecosystems: Deep expertise in deploying and managing data infrastructure on cloud platforms (AWS, Azure, or GCP). Proficient in Infrastructure as Code (Terraform/CloudFormation) and establishing end-to-end CI/CD pipelines for data solutions.
• Advanced Data Modeling: Strong skills in conceptual, logical, and physical data modeling, with the ability to balance data normalization, query performance, and safely manage complex schema migrations in production.
• AI/MLOps Readiness: Mastery of incorporating AI tools to optimize data engineering workflows and the ability to design data validation and evaluation frameworks that support the deployment and governance of AI/ML models.
• Full-Stack Solution Delivery: Capability to rapidly prototype and build complete, end-to-end data applications across diverse technology stacks, prioritizing solution speed and business value while effectively managing technical debt.
• System Reliability & Resilience (SRE): Direct experience defining and monitoring service level objectives (SLOs/SLIs). A track record of designing highly resilient data systems that ensure graceful degradation and driving post-incident improvements.
• Architectural Leadership: Ability to make sound architectural trade-offs, design scalable system components, and produce high-quality, well-tested code that adheres to enterprise standards.

Who you are

• Polymath Oriented: You bridge gaps between engineering, design, business, and science, rapidly immersing yourself in new domains to speak the language of the business.
• Curious Explorer: You seek out ambiguity rather than avoiding it, driving team curiosity through challenging questions and creating an environment that encourages experimentation.
• Outcome Owner: You drive an accountability culture focused on business impact rather than just deliverables, owning relationships and making trade-offs between custom solutions and generalizable work.
• Systems Thinker: You map complex system interactions across technical and business domains, anticipating cascading effects and understanding how technology changes impact operations.
• Precise Communicator: You translate seamlessly between technical and business language, ensuring requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders.
• Problem Discoverer: You embed with users to discover latent needs, turning ambiguity into clear problem statements rather than waiting for defined tasks.

What Appnovation Offers 

• Challenging and rewarding work with real impact
• Direct Access to Cutting-Edge AI Platforms
• Diverse and Inclusive Culture 
• Growth opportunities for personal and professional development
• A collaborative and innovative work environment where your ideas are valued
• Exposure to exciting projects and high-profile clients
• Supportive work environment with access to company leaders
• Hybrid working model