Grupo QuintoAndar | Senior Data Engineer

About Grupo QuintoAndar We are Grupo QuintoAndar, the largest real estate ecosystem in Latin America. Guided by a shared purpose of helping people love where they live, we have a diversified portfolio of brands and solutions across different countries in Latin America, covering all phases of the housing journey. We also have a Technology Hub in Portugal. We develop technology and innovation to transform and enhance the overall living experience. With the support of a world-class team of investors and advisors, including Kaszek, Qualcomm, General Atlantic, and SoftBank, Grupo QuintoAndar is currently valued at over USD 5.1 billion and continues to grow year over year. Here, you will work with top professionals in the market, in an environment that breathes innovation, collaboration, and high performance. To learn more about our story, visit: https://grupoquintoandar.com/pt/ . Location & Remote Work Our technology team operates under a "remote-first" model, which means we work from home and can live anywhere in Brazil. We also offer the option of working from our São Paulo offices or partner coworking spaces, up to twice a week. Hiring Process Stages The stages of our hiring processes aim to assess your experiences and allow you to meet our teams and explore career opportunities. They are structured as follows: Application Interview with Recruiter Tech Screening Technical Interviews with Data Team Offer About the Role We are looking for a skilled and motivated Data Engineer Specialist to join our team. The responsibilities of this role is to design, build, and maintain a robust, self-service, scalable, and secure data platform and end-to-end data pipelines that empowers Data Analysts, and Data Scientists to deliver insights and drive strategic decision-making. Responsibilities of a Data Engineer at QuintoAndar: 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. What we are looking for: Has 7 or more years of experience in Data Engineering roles; 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, with experience working on data-centric systems; Experience with columnar storage solutions and/or data lakehouse concepts; Proficiency in Python, or one of the main programming languages, and a passion for writing clean and maintainable code.