Data Engineer

About the role

ABOUT AIR APPS

At Air Apps, we believe in thinking bigger—and moving faster. We’re a family-founded company on a mission to create the world’s first AI-powered Personal & Entrepreneurial Resource Planner (PRP), and we need your passion and ambition to help us change how people plan, work, and live. Born in Lisbon, Portugal in 2018—and now with offices in both Lisbon and San Francisco—we’ve remained self-funded while reaching over 100 million downloads worldwide.

Our long-term focus drives us to challenge the status quo every day, pushing the boundaries of AI-driven solutions that truly make a difference. Here, you’ll be a creative force, shaping products that empower people across the globe.

Join us on this journey to redefine resource management—and change lives along the way.

THE ROLE

As a Data Engineer at Air Apps, you will be responsible for designing, building, and optimizing data pipelines, data warehouses, and data lakes to ensure efficient data processing and analytics. You will work closely with data analysts, scientists, and software engineers to create scalable and reliable data infrastructure that supports business intelligence and machine learning initiatives.

This role requires expertise in data architecture, ETL processes, and cloud-based data solutions to handle large volumes of structured and unstructured data.

RESPONSIBILITIES

- Design, build, and maintain scalable data pipelines and ETL workflows to support analytics and reporting.

- Develop and optimize data warehouses and data lakes using cloud platforms such as AWS, Google Cloud, or Azure.

- Implement real-time and batch data processing solutions for various business needs.

- Work with structured and unstructured data, ensuring proper data modeling and storage strategies.

- Ensure data reliability, consistency, and scalability through best practices in architecture and engineering.

- Collaborate with data analysts, scientists, and software engineers to enable efficient data access and analysis.

- Automate data ingestion, transformation, and validation processes to improve data quality.

- Monitor and optimize query performance and data processing efficiency.

- Implement security, compliance, and governance standards for data storage and access control.

- Stay up to date with emerging data engineering trends, tools, and technologies.

REQUIREMENTS

- Around 4+ years of experience in data engineering, software engineering, or database management.

- Proficiency in SQL, Python, or Scala for data processing and automation.

- Hands-on experience with cloud-based data solutions (AWS Redshift, Google BigQuery, Azure Synapse, Snowflake).

- Experience building ETL pipelines with tools such as Apache Airflow, dbt, Talend, or Fivetran.

- Strong understanding of data modeling, schema design, and database optimization.