Grupo QuintoAndar | Staff Data Engineer

About the role

You will design, build, and maintain a robust, self-service, scalable, and secure data platform and end-to-end data pipelines that empower Data Analysts and Data Scientists to deliver insights and drive strategic decision-making. You will create and edit data pipelines, considering business logic that best applies to the area in question, choosing levels of aggregation, grouping and transforming fields, checking data quality, and cleaning the data. You will create data modeling and transformation workflows, enabling the creation of clear and accessible data abstractions. You will be responsible for the entire code development lifecycle, including monitoring deployment, documentation, performance, security, adding metrics and alarms, and ensuring SLO budget compliance. You will investigate inconsistencies and be able to trace the source of differences in data troubleshooting. You will enable teams across the company to access and use data more effectively through self-service tools and well-modeled datasets. You will align with stakeholders to understand their primary needs, while also having a holistic view of the problem and proposing extensible, scalable, and incremental solutions. You will conduct PoCs and benchmarks to determine the best tool for a given problem, and decide whether to use an off-the-shelf solution or develop one in-house.

Key facts

What you'll do

• Build and maintain a high-performance data platform that meets the company's needs, connects with product solutions, and leads analytical innovation, enabling incredible architectures and efficient platforms.
• Create and edit data pipelines, considering business logic that best applies to the area in question, choosing levels of aggregation, grouping and transforming fields, checking data quality, and cleaning the data.
• Create data modeling and transformation workflows, enabling the creation of clear and accessible data abstractions.
• Responsible for the entire code development lifecycle (monitoring deployment, documentation, performance, security, adding metrics and alarms, ensuring SLO budget compliance, and more).
• Investigate inconsistencies and be able to trace the source of differences (data troubleshooting).
• Enable teams across the company to access and use data more effectively through self-service tools and well-modeled datasets.
• Align with stakeholders to understand their primary needs, while also having a holistic view of the problem and proposing extensible, scalable, and incremental solutions.
• Conduct PoCs and benchmarks to determine the best tool for a given problem, and decide whether to use an off-the-shelf solution or develop one in-house.
• Contribute to defining the strategic vision, crossing team and service boundaries to solve problems.
• Advocate for the value of data analytics and engineering within the organization and fostering a data-driven culture.
• Be a reference within the chapter on technical concepts, tools, and/or best coding practices.

Requirements

• Specialist in technologies, solutions, and concepts of Big Data (Spark, Hadoop, Hive, MapReduce) and multiple languages (YAML, Python).
• Experience with Airflow, Spark, AWS and Databricks.
• Strong foundation in software engineering principles, distributed systems, and data modeling.
• Experience with version control systems, testing frameworks, and infrastructure as code.
• Understanding of data security, privacy, and governance concepts.
• Proven ability to collaborate with cross-functional teams and communicate effectively with both technical and non-technical stakeholders.
• Commitment to continuous learning and improvement in a fast-paced, high-growth environment.
• Willingness to work within the constraints and opportunities of a remote-first culture that values autonomy and ownership.

Nice to have

• Preferred experience working in technology companies or fast-paced, high-growth environments.
• Familiarity with real estate or property-related data domains.
• Contributions to open-source data projects or public repositories.
• Experience with cloud cost optimization and observability practices.
• Knowledge of data visualization tools and storytelling with data.

Practical notes

• This role operates under a remote-first model, which means you can work from home and live anywhere in Brazil.
• You have the option to work from our São Paulo offices or partner coworking spaces, up to twice a week.
• The hiring process includes the following stages: Application, Interview with Recruiter, Tech Screening, Technical Interviews with Data Team, and Offer.
• The selection process is designed to assess your experience and allow you to meet our teams and explore career opportunities.