About the role

We're looking for a Data Engineer to own the data foundations behind our work — from strategy and governance to the pipelines, warehouses, and integrations that keep reliable, high-quality data flowing. You'll partner closely with analysts and data scientists, raise the bar for quality and security, and help grow a high-performing data team.

What you'll do

Define and execute a comprehensive data strategy aligned with the company's goals and long-term vision.
Establish data-related KPIs and build a clear roadmap for data operations and initiatives.
Implement and oversee data governance policies to ensure data quality, security, and regulatory compliance.
Manage data acquisition and ingestion processes, ensuring accuracy, completeness, and timeliness of data from multiple sources.
Design, manage, and optimize data warehousing solutions to guarantee scalability, availability, and performance.
Define and monitor data quality metrics, implementing validation and cleansing processes across data assets.
Lead data integration efforts to ensure seamless data flow between systems and teams.
Collaborate closely with data analysts and data scientists, enabling high-quality analytics and informed decision-making.
Lead, mentor, and grow a team of data professionals, fostering a high-performance and collaborative culture.
Evaluate emerging data technologies and tools, recommending and implementing improvements to the data stack.
Implement robust data security practices to protect sensitive information and prevent data breaches.
Prepare and present reports on data operations, quality, and performance metrics to senior leadership.

What we're looking for

5+ years of hands-on experience with SQL and Python.
Strong knowledge of data management, data warehousing, ETL processes, and data governance best practices.
Experience working with data analytics and business intelligence tools.
Excellent analytical, problem-solving, and communication skills.
Advanced English, both spoken and written.

Nice to have

Experience with cloud-based data platforms such as AWS, Snowflake, Databricks, or similar.
Knowledge of big data paradigms and technologies (e.g., MapReduce).
Previous experience in data-intensive industries like finance, e-commerce, or high-scale digital products.
Background working with complex, high-volume datasets.

Location & work model

Montevideo, Uruguay. Three days a week in-office during onboarding, then a flexible hybrid model.

Benefits

Flexible work: hybrid with remote options and flexible hours.
Continuous learning & development: trainings, conferences, mentorship, and company-supported English classes.
An inclusive, collaborative, pet-friendly culture where your ideas shape Streaver's growth.