Data & ML Platform Engineer

Tekever; United States; Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Meal allowance

Health insurance

Employee assistance program (EAP)

Job summary

Tekever is seeking a Data & ML Platform Engineer to design, build, and maintain the infrastructure powering data processing and ML workflows. You will operate at the intersection of data engineering, MLOps, and platform development to ensure a robust, scalable, and efficient Data & AI Platform.

The role requires 3+ years in data/ML platform engineering, strong Python/Go/Java/Rust skills, and expertise in Docker/Kubernetes, cloud data services, and observability tooling.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field.
• 3+ years of experience in data & ML platform engineering or similar role.
• Proficiency in Python, Go, Java, or Rust.
• Strong knowledge of Docker and Kubernetes in production environments.
• Experience with SQL and data modeling, cloud platforms (AWS/Azure/GCP) and data services.
• Familiarity with Spark, data warehousing (Redshift/Snowflake), Airflow, and CI/CD.
• Experience with observability stacks (Prometheus, Grafana, Loki, ELK) and IaC (Terraform/Ansible).
• Interest in AI-assisted development and data/ML platform components.

Responsibilities

• Design and build scalable data and ML infrastructure for pipelines and workflows.
• Develop scalable data pipelines to collect, process and store large data volumes.
• Manage databases and data warehouses for performance and availability.
• Integrate data from APIs, databases, and external providers into unified datasets.
• Create self-service tools for insights from data and ML models.
• Support expansion of Data & AI Platform and ensure security/compliance.
• Implement observability, monitoring and cost optimization for data systems.
• Collaborate with data scientists and analysts to meet platform requirements.
• Document platform components, APIs and workflows for adoption.
• Design and manage MLOps pipelines for model training, deployment and monitoring.

Skills

Python

Go

Java

Rust

Docker

Kubernetes

SQL

PostgreSQL

AWS

Azure

GCP

Airflow

Redshift

Snowflake

ETL

CI/CD

GIT

Observability

Prometheus

Grafana

Loki

ELK

Terraform

Ansible

MLOps

AI tools

Education

Bachelor’s or Master’s in Computer Science/Engineering/Information Systems

Tools

Docker

Kubernetes

Terraform

Ansible

Airflow

Snowflake

Redshift

Job description

Mission:

As a Data & ML Platform Engineer, you will play a critical role in designing, building and maintaining the infrastructure that powers our data processing pipelines and machine learning workflows that support our data‑driven initiatives, as well as supporting the evolution of our Data & AI Platform. You will work at the intersection of data engineering, MLOps, and platform development and ensure that our data & AI infrastructure is robust, scalable and efficient. The ideal candidate will have a strong background in platform engineering, with experience in data science, machine learning and or data engineering.

What will be your responsibilities:

• Data and ML infrastructure: Design and implement scalable data and ML infrastructure using modern cloud and on‑prem distributed technologies and frameworks.


• Data Pipeline Development: Design, develop and maintain scalable and efficient data pipelines to collect, process and store large volumes of data from various sources.


• Database Management: Manage and optimize databases and data warehouses to ensure data integrity, performance and availability.


• Data Integration: Integrate data from multiple sources, including APIs, databases and external data providers, to create unified datasets for analysis.


• Self‑Service Tools: Develop self‑service tools that enable stakeholders to extract insights from Data and Machine Learning models.


• Data & AI Platform development & expansion: support the expansion of our Data & AI Platform.


• Security & Compliance: Ensure data security, privacy, and compliance.


• Data Quality Assurance: Implement data validation and quality assurance processes to ensure the accuracy and consistency of data.


• Collaboration: Work closely with data scientists, analysts and other stakeholders to understand platform requirements and provide the necessary data infrastructure and support.


• Monitoring & Performance Optimization: Implement monitoring, observability, and alerting for data and ML systems and optimize for performance, reliability, and cost‑effectiveness.


• Documentation: Maintain comprehensive documentation of platform components, APIs, and workflows to ensure knowledge sharing and user adoption (e.g. data pipelines,database schemas, Machine Learning systems, etc.).


• Design and manage MLOps pipelines to support model training, deployment and monitoring at scale.


• Design and manage MLOps pipelines to support model training, deployment and monitoring at scale.


• Experience implementing observability stacks and logging pipelines (e.g., Prometheus, Grafana, Loki, ELK).


• Experience with IaC frameworks (e.g. Ansible, Terraform),


• Understanding of DevOps best practices and tools: GIT, CI/CD, telemetry and monitoring, etc.


• Affinity, experience with & strong openness to AI-assisted development with tools such as Claude, Claude Code, Cursor or Copilot – e.g. building and maintaining data and ML platform components, infrastructure-as-code and CI/CD workflows, and generating tests and documentation – with the judgement to review, test and verify what they produce. Additional training can be provided in‑house, but affinity, some form of experience & strong openness to these new ways of working are essential.


• Analytical Skills: Strong analytical and problem‑solving skills with a focus on delivering scalable and efficient data solutions.


• Communication: Excellent verbal and written communication skills, with the ability to effectively collaborate with technical and non‑technical stakeholders.


• Attention to Detail: High attention to detail and a commitment to ensuring data quality and accuracy.


• Adaptability: Ability to work in a fast‑paced, dynamic environment and manage multiple priorities simultaneously.


• Location: Being located in Portugal, UK or France is a bonus.

Profile and requirements:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.


• Experience: 3+ years of experience in data & ML platform engineering or a similar role.


• Proficiency in programming languages such as Python, Go, Java, or Rust.


• Strong knowledge of containerization technologies (e.g. Docker) and orchestration systems (e.g. Kubernetes) in production environments.


• Experience with SQL,database management systems (e.g., MySQL, PostgreSQL, SQL Server), data modeling and schema design.


• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services, with a focus on Google Cloud. Google Cloud certification is preferred.


• Familiarity with big data technologies (e.g.Spark),data warehousing solutions (e.g., Redshift, Snowflake), data pipeline orchestration (e.g. Airflow), and database systems (SQL and noSQL).


• Design and manage MLOps pipelines to support model training, deployment and monitoring at scale.


• Design and manage MLOps pipelines to support model training, deployment and monitoring at scale.


• Experience implementing observability stacks and logging pipelines (e.g., Prometheus, Grafana, Loki, ELK).


• Experience with IaC frameworks (e.g. Ansible, Terraform),


• Understanding of DevOps best practices and tools: GIT, CI/CD, telemetry and monitoring, etc.


• Affinity, experience with & strong openness to AI-assisted development with tools such as Claude, Claude Code, Cursor or Copilot – e.g. building and maintaining data and ML platform components, infrastructure-as-code and CI/CD workflows, and generating tests and documentation – with the judgement to review, test and verify what they produce. Additional training can be provided in‑house, but affinity, some form of experience & strong openness to these new ways of working are essential.


• Analytical Skills: Strong analytical and problem‑solving skills with a focus on delivering scalable and efficient data solutions.


• Communication: Excellent verbal and written communication skills, with the ability to effectively collaborate with technical and non‑technical stakeholders.


• Attention to Detail: High attention to detail and a commitment to ensuring data quality and accuracy.


• Adaptability: Ability to work in a fast‑paced, dynamic environment and manage multiple priorities simultaneously.


• Location: Being located in Portugal, UK or France is a bonus.

What we have to offer you

• A dynamic and collaborative working environment, with the opportunity to make a real impact


• A competitive salary package, aligned with your proven level of experience


• Meal allowance and health insurance for employees


• Bonus in line with company policy


• Access to the Employee Assistance Programme (EAP)

Pre-Employment Requirements

Employment offers may be contingent upon successful completion of a background check and reference verification, in accordance with applicable laws and company policy.

Equal Employment Opportunity

TEKEVER is an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex (including pregnancy, sexual orientation, gender identity, and gender expression), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by federal, state, or local law.

Do you want to know more about us ?

Visit our LinkedIn page at https://www.linkedin.com/company/tekever/