Freelance Senior Data Engineer

The role

We’re looking for a Freelance Senior Data Engineer to join our innovative Data Platform team, a core component of Recharge’s ambitious goals. In this role, you’ll be integral to designing, building, and maintaining scalable data pipelines that fuel decision-making across the business. You’ll work closely with product, engineering, and analytics teams to ensure data is accessible, reliable, and impactful. You will work alongside other 2 Data Engineers and report directly to

Oberdan Bitencourt Ferreira.

Requirements

What will you be working on:

• Design and implement robust data pipelines to support both batch and real-time data processing, ensuring optimal performance and scalability.

• Collaborate with cross-functional teams to gather requirements, develop ETL processes, and deliver high-quality data products for analytics and machine learning.

• Own end-to-end data workflows, from ingestion through transformation to delivery, ensuring data accuracy, consistency, and accessibility.

• Identify and implement best practices for data engineering, data quality, and data governance, continuously improving our platform.

• Develop monitoring and alerting mechanisms to detect and resolve issues within the data infrastructure proactively.

• Work with cloud services, particularly AWS, to build, manage, and optimise data lakes and warehouses.

• Contribute to designing and enforcing Recharge’s data architecture, policies, and processes.

• Mentor and collaborate with less experienced engineers, fostering a culture of knowledge sharing and continuous learning.

• Participate in roadmap development, proactively proposing innovative data solutions aligning with business objectives.

What You Have:

• 5+ years of experience in data engineering, building data pipelines, and managing ETL workflows at scale.

• Strong hands-on experience with data processing frameworks and languages like SQL and Python.

• Solid understanding of cloud environments, especially AWS, focusing on services like S3 and AWS Step Functions.

• Solid experience with AWS Redshift.

• Knowledge or experience with SaaS tools such as Airbyte, Fivetran, dbt, Sifflet, Spark/PySpark or similar tools.

• Experience with containerisation solutions like Docker.

• Proven expertise in designing, building, and managing data lakes, data warehouses, and other data infrastructure solutions with or without using SaaS applications.

• Solid understanding of workflow management tools like Apache Airflow.

• Experience with data quality management, monitoring, and observability best practices to ensure data reliability.

• Experience with defining/maintaining CI/CD for data pipelines, including automated testing, environment provisioning and other best practices. We rely on GitHub Actions and Terraform.

• Ability to collaborate and communicate effectively with technical and non-technical stakeholders, aligning data initiatives with business goals.

• A self-starter with strong problem-solving skills, continually seeking ways to optimise and innovate in data engineering processes.

• Ability to operate responsibly in alignment with the industry's best practices and team conventions. The ability to drive initiatives toward completion and deliver working solutions is a must-have.