Offer summary

Qualifications:

At least 3 years of experience as a Data Engineer or similar role., Proficiency in SQL and Python programming., Experience with ETL/ELT tools, workflow orchestrators like Airflow or Prefect, and data warehouses such as BigQuery, Redshift, or Snowflake., Solid understanding of data architecture, modeling, and best practices in data engineering..

Key responsibilities:

Design, build, and maintain scalable data pipelines.

Ensure data quality, consistency, and availability for various teams.

Collaborate with stakeholders to understand data needs and facilitate access.

Manage data workflows and participate in defining data architecture for new features.

Job description

Workana is the largest remote work platform for talents in Latin America. Our new segment, Workana Premium, focuses on matching the most exceptional professionals with leading and innovative companies around the globe. Enjoy competitive compensation, dedicated support, and the flexibility of remote work within a dynamic environment that fosters collaboration and professional advancement.

We are proud to present you with the following opportunity.

Role Overview:

As a Data Engineer at Workana, you will be responsible for designing, building, and maintaining a robust and scalable data infrastructure. You will play a critical role in ensuring the integrity, availability, and efficiency of our data systems, empowering the organization to make informed, data-driven decisions. This role requires a strong combination of technical expertise and pragmatic business thinking.

Responsibilities:

Design, build, and maintain efficient and scalable data pipelines.
Ensure data quality, consistency, and availability for product, business, and IT teams.
Collaborate with Product Data Analysts and other stakeholders to understand data needs and enable access to relevant information.
Manage workflow orchestration tools and databases (ETLs, data lakes, data warehouses).
Participate in defining data architecture for new functionalities or structural product changes.
Quickly and accurately troubleshoot issues in existing data pipelines.

Requirements

3+ years of experience as a Data Engineer or in similar roles.
Strong proficiency in SQL and Python.
Experience with ETL/ELT tools, workflow orchestrators (e.g., Airflow, Prefect), and data warehouses (e.g., BigQuery, Redshift, Snowflake).
Solid understanding of data architecture, modeling, and best practices in data engineering.
Ability to prioritize tasks with a focus on impact, scalability, and simplicity.
Pragmatic mindset: we value an 80/20 approach well-executed over academic perfection.
Passion for solving complex problems and building simple, effective solutions.
Strong collaboration, communication skills, and eagerness to learn.

Benefits