Coderio designs and delivers scalable digital solutions for global companies.
We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end.
We work with international clients, value autonomy and clear communication, and build long‐term partnerships through technical excellence.
More information: This is a high-impact technical role.
We are looking for a motivated and adaptive DataOps Engineer, Technical Referent to join our fast-paced environment.
You will operate at the intersection of data engineering, cloud infrastructure, and DevOps, where a high tolerance for ambiguity and a passion for constant learning are essential.
Your primary mission involves interacting with customers to understand their needs, extract requirements, and both design and propose scalable solutions.
You will be responsible for tackling the challenge of working within a team to develop solutions, as well as executing hands‐on technical work to ensure robust data operations.
What To Expect In This Role (Responsibilities) Automation & Integration: Develop Python components, Terraform modules, and pipelines to integrate and automate various tools and processes.
API & System Orchestration: Promote the use of APIs from distinct systems to extract and update data, trigger and monitor processes, and help tie infrastructures together.
Cloud Reliability & Operations: Deploy, maintain, and oversee cloud infrastructure to ensure it runs with the performance and reliability our customers expect.
Data Modeling & Documentation: Help create Data Models, technical documents, and best practices for our users.
DataOps Best Practices & Innovation: Develop policies, processes, and best practices regarding DevOps and DataOps.
You will also help identify opportunities, generate innovative solutions, and improve existing product features.
Requirements Development & Scripting: Strong proficiency in Python and bash, and fluency in SQL as a second language.
Data Ecosystems & Pipelines: Deep familiarity with databases, data warehouses, and data lakes, as well as being adept at data pipelines and process improvement.
Cloud & Tooling Mastery: Strong knowledge of AWS environments, including EC2, Lambda, IAM, SQS, RDS, Kinesis, Glue, and EKS.
Must also be familiar with modern development tools like Terraform, GitHub, Docker, and dbt.
Mindset & Work Style: Ability to thrive in an environment with constant and quick iterations, consistently seeking out creative solutions to challenging problems.
Must have strong attention to detail.
Autonomy & Collaboration: Ability to work collaboratively while also being capable of owning a project with little guidance.
Must be comfortable working in a diverse environment and non‐hierarchical organizations.
Customer‐Facing Skills: Ability to interact directly with customers to understand needs, extract requirements, and propose technical solutions.
Nice to Have AWS associate or professional‐level certifications, such as Solutions Architect, Developer, or DevOps Engineer.
High‐impact, strategic role driving modern data infrastructure and automation.




Cuitment agency with a strong presence across the Americas and Europe.
We specialize in connecting companies with exceptional professionals across data, analytics, and business functions.
We have partnered with a U.S.-based company specialized in marketing effectiveness measurement.
They help organizations better understand consumer behavior, purchasing trends, brand performance, and market dynamics through data-driven insights.
We are looking for a Data Analyst (Machine Learning) to join our client's global team.
This role is ideal for analytical and data-driven professionals who enjoy working with large-scale consumer and retail datasets, bridging the gap between complex database structures and business strategy, and turning raw transactional or behavioral data into clear, actionable metrics.
The ideal candidate combines solid SQL and Python skills, a strong "numbers sense", attention to detail, and the ability to translate technical results into clear summaries for stakeholders in English.
The position is open to a range of experience levels, from recent graduates with a strong quantitative background to mid-level analysts looking to deepen their technical data manipulation skills.
About Us
Prometeo Talent is a recruitment agency with a strong presence across the Americas and Europe.
We specialize in connecting companies with exceptional professionals across data, analytics, and business functions.
We have partnered with a U.S.-based company specialized in marketing effectiveness measurement.
They help organizations better understand consumer behavior, purchasing trends, brand performance, and market dynamics through data-driven insights.
We are looking for a Data Analyst (Machine Learning) to join our client's global team.
This role is idóneo for analytical and data-driven professionals who enjoy working with large-scale consumer and retail datasets, bridging the gap between complex database structures and business strategy, and turning raw transactional or behavioral data into clear, actionable metrics.
The ideal candidate combines solid SQL and Python skills, a strong "numbers sense", attention to detail, and the ability to translate technical results into clear summaries for stakeholders in English.
The position is open to a range of experience levels, from recent graduates with a strong quantitative background to mid-level analysts looking to deepen their technical data manipulation skills.
What You Will Do
Write, optimize, and execute SQL queries to extract data from relational databases and cloud data warehouses.
Develop, run, and validate machine learning, predictive, or statistical matching models to uncover deeper consumer behaviors and forecast trends.
Slice, unpivot,



and aggregate raw transactional or panel data to calculate core business metrics such as household penetration, market share, and purchasing trends.
Build and maintain clean, structured data tables and views that feed into recurring tracking reports and stakeholder dashboards.
Review query outputs, perform data audits, and double-check logic to ensure accuracy and data integrity before insights are finalized.
Use conditional logic and filtering techniques to segment data and isolate specific tracking cohorts.
Clean, parse, and categorize unstructured or semi-structured text data.
Translate technical data structures and query results into clear written summaries, bullet points, or data tables for stakeholders in English-speaking environments.
Requirements
0 to 4 years of experience in Data Analysis, Business Analytics, or similar roles.
Entry-level candidates with strong relevant coursework, personal data projects, or internships are welcome, as well as mid-level professionals with a proven track record of querying databases to drive business insights.
Advanced English level (written and spoken).
Foundational to intermediate SQL skills, including complex JOIN logic, standard aggregations, and CASE WHEN conditional logic.
Python scripting for data cleaning, manipulation, and processing, with proficiency in pandas for complex multi-step transforarchitectures, and modern software engineering practices .
Develop backend services primarily using Python and/or Go .
Work with SQL and NoSQL databases to store, transform, query, and analyze high‐volume data.
Build and operate containerized services using Docker and Kubernetes .
Deploy and integrate solutions across AWS, Azure, and GCP environments .
Troubleshoot complex customer deployment and integration issues across application, infrastructure, networking, API, and data layers.
Optimize ingestion performance, reliability, scalability, and operational efficiency.
Collaborate with Solution Architects, Sales Engineering, Customer Success, Product, and Engineering teams.
Act as a trusted technical advisor around customer data architecture, collection strategies, security integrations, and implementation best practices.
Identify recurring customer requirements and transform them into reusable connectors, platform capabilities, or improvements to the core product.
Contribute technical insights from real‐world implementations to the product roadmap.
Support production adoption and continuously improve time‐to‐value for enterprise customers.
Participate in occasional customer‐facing technical sessions and, when necessary, onsite engagements.
What You Bring 10+ years of professional Software Engineering, Data Engineering, Platform Engineering, or related experience.
Strong software development experience with: Python Go Strong experience designing and consuming REST APIs .
Hands‐on experience building data ingestion pipelines, connector frameworks, integration platforms, or similar systems .
Experience integrating complex enterprise systems and third‐party platforms.
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📌 Senior Data Engineer (Santa Fe)
🏢 Jampp
📍 Santa Fe