Data Engineer (Snowflake)

UST; United States; Remote; USD 51,000 - 101,000; Full time

Benefits offered by this job

Health care plan

Teleworking compensation

Career development programs

Referral bonuses

Flexible payments 12 or 14 times per 0

Job summary

UST is hiring a focused Software/Data Engineer to build and support our Data Platform. The role combines data engineering with modern CI/CD practices, cloud deployments, and AI-enabled development.

You will work across Snowflake, dbt, Azure Data Factory, and Python to deliver reliable data solutions while collaborating with stakeholders and production teams. Remote work is available (Spain) with standard business hours.

Qualifications

• Strong experience with SQL, Snowflake and data engineering concepts.
• Knowledge of dimensional modeling (Kimball) including facts, dimensions and grain.
• Hands-on experience with dbt models and CI/CD practices.
• Proficient in Python for data engineering tasks and testing.
• Experience with Generative AI tools and AI-enabled solutions.
• Familiarity with Azure DevOps or GitHub and cloud deployments.
• Power BI semantic models and data consumption patterns.

Responsibilities

• Design, develop and maintain Snowflake data models, transformations, views and pipelines.
• Build and enhance dbt models with testing, documentation and deployment.
• Develop and maintain ETL/ELT workflows and data integrations.
• Support Azure Functions, Data Factory, Pipelines and deployments.
• Create Python utilities and tooling for data processing and testing.
• Work with GitHub or Azure DevOps, handle PRs, code reviews and CI/CD.
• Maintain production systems, investigate incidents and perform root cause analysis.
• Contribute to AI-enabled solutions and leverage GitHub Copilot.
• Support .NET/C# services and collaborate on React/TypeScript apps when needed.
• Collaborate with engineers, analysts and stakeholders to translate requirements.

Skills

SQL

Snowflake

Data engineering

Dimensional modeling

dbt

Azure Data Factory

Azure Functions

Azure Pipelines

Python

Generative AI

Power BI

GitHub/Azure DevOps

CI/CD

React/TypeScript

Tools

dbt

Power BI

Snowflake

Azure Data Factory

Azure Functions

Azure Pipelines

GitHub

Job description

We are looking for the very Top Talentand we would be delighted if you were to join our team More in details UST is a multinational company based in North America certified as a Top Employer and Great Place to Work company with over 35.000 employees all over the world and presence in more than 35 countries. We are leaders on digital technology services and we provide large-scale technologic solutions to big companies.

What we look for

We are looking for a practical and hands-on Software/Data Engineer to help build modernize and support the Client Group Data Platform. The ideal candidate combines strong data engineering expertise with a structured and proactive approach to problem-solving capable of delivering reliable solutions from clear requirements while supporting production environments effectively. The successful candidate will have solid experience in Snowflake SQL Python Azure Data Factory Generative AI and Power BI together with knowledge of modern development practices CI/CD processes and cloud-based data solutions. They should be comfortable working independently on well-defined tasks collaborating with stakeholders and contributing to continuous improvement initiatives.

Main tasks and accountabilities

• Design develop and maintain Snowflake data models transformations views and data pipelines.
• Build and enhance dbt models including testing documentation and deployment processes.
• Develop and maintain ETL/ELT workflows and data integration solutions.
• Support and manage Azure Functions Azure Data Factory Azure Pipelines and deployment activities.
• Create Python-based utilities automation tools and services for data processing testing and troubleshooting.
• Work with source control systems such as Azure DevOps or GitHub including pull requests code reviews and CI/CD pipelines.
• Maintain and support production systems investigate incidents perform root cause analysis and improve operational support capabilities.
• Contribute to AI-enabled solutions and leverage tools such as GitHub Copilot to improve productivity code quality and documentation.
• Support and maintain existing .NET/C# services and occasionally contribute to React/TypeScript applications.
• Collaborate with engineers analysts and business stakeholders to translate requirements into scalable and maintainable solutions.
• Support data platforms that enable reporting analytics Power BI dashboards client insights semantic models and AI-driven use cases.

What do we expect from you

Technical Skills

• Strong experience with SQL Snowflake and data engineering concepts.
• Good understanding of dimensional modeling (Kimball methodology) including facts dimensions grain historical data and conformed dimensions.
• Experience building and maintaining dbt models and applying engineering best practices.
• Hands-on experience with Azure Data Factory Azure Functions Azure Pipelines and cloud-based deployments.
• Strong programming skills in Python for data engineering automation testing and integrations.
• Experience with Generative AI tools and AI-enabled solution development.
• Familiarity with version control platforms such as Azure DevOps or GitHub and CI/CD methodologies.
• Knowledge of Power BI semantic models and data consumption patterns.

Nice to Have

• Experience with .NET/C# xUnit or similar testing frameworks.
• Knowledge of React TypeScript Vite React Query MSAL and OAuth authentication.
• Advanced Snowflake capabilities such as Snowpipe Streams Tasks Secure Views and performance tuning.
• Experience within Financial Services Asset Management Marketing or Client Services environments.
• Understanding of metadata management lineage and modern data products.

Soft Skills

• Takes ownership and delivers high-quality work with minimal supervision.
• Communicates clearly and raises issues or blockers early.
• Approaches problems logically and explains technical concepts in a simple manner.
• Balances delivery speed with quality testing governance and maintainability.
• Works collaboratively with technical and non-technical stakeholders.
• Demonstrates curiosity adaptability continuous learning and a commitment to improving team practices.

Work Location

100 remote (Spain)

Work Schedule

Business hours.

What can we offer

• 23 days of Annual Leave plus the 24th and 31st of December as discretionary days Numerous benefits (Health Care Plan teleworking compensation Life and Accident Insurances).
• Retribución Flexible Program (Meals Kinder Garden Transport online English lessons Health Care Plan)
• Free access to several training platforms Professional stability and career plans UST also compensates referrals from which you could benefit when you refer professionals.
• The option to pick between 12 or 14 payments along the year.
• Real Work Life Balance measures (flexibility WFH or remote work policy compacted hours during summertime) UST Club Platform discounts and gym Access discounts