Senior Data Engineer

Há 18 horas


Mato Grosso, Brasil Eightpoint Tempo inteiro

About Eightpoint Eightpoint is an internet technology company specializing in the agile development of products and content that address real-world interests, captivating users and driving significant growth for partners. With offices in the United States and Cayman Islands, Eightpoint collaborates with partners globally on the next generation of user-centric offerings. Our growing ecosystem includes innovative products like Weather Now, a sleek app that delivers real-time forecasts with clarity and ranks among the top three most-used weather apps in the U.S.; Check Heart Rate Now, aquick and easy wellness monitor; and Wave Browser, a powerful and secure way to search the web. Every product we launch is designed to engage users, enhance daily life, and deliver real-world value. Backed by data and driven by a relentless commitment to quality, Eightpoint moves fast, thinks big, and builds digital experiences that people love. About the Role We are seeking a Full-Stack Data Engineer to join our Mobile Applications department. This is a hybrid role that combines data engineering with data science overlap, giving you full ownership of the data lifecycle — from ingestion to transformation, analysis, and storytelling. You will build and optimize scalable pipelines, ingest mobile app data from diverse sources, ensure infrastructure reliability, and deliver insights that directly influence how our apps grow. The ideal candidate thrives at the intersection of engineering and analytics, equally capable of writing production-grade pipelines and uncovering meaningful trends in user behavior. Key Responsibilities Data Infrastructure & Pipelines Build and maintain scalable, end-to-end pipelines across cloud environments. Ingest and transform data from files, APIs, mobile telemetry (Firebase, Amplitude, Google Analytics), and external databases into centralized stores. Continuously monitor, troubleshoot, and optimize infrastructure for performance, scalability, and cost-effectiveness. Implement data quality monitoring, governance policies, and best practices for privacy, security, and compliance. Participate in technical architecture discussions, contributing expertise on scalable, efficient data systems. Analytics & Insights Conduct exploratory and advanced analysis using SQL, Python, and statistical methods. Collaborate with Analysts, Data Scientists, and Product Managers to translate business requirements into technical solutions. Support experimentation and A/B testing by ensuring clean, reliable datasets and analyzing results. Deliver actionable recommendations that influence mobile product strategy, user acquisition, and retention. Collaboration & Best Practices Engage in peer code reviews to uphold high standards of quality and maintainability. Work cross-functionally with software engineering and business teams to ensure data solutions align with company priorities. Document pipelines, workflows, and methodologies to foster reusability and knowledge sharing. Who You Are Bachelor's degree in Computer Science, Engineering, or related field. 3+ years of experience as a Data Engineer or in a similar technical role focused on data infrastructure and pipelines. Strong expertise in SQL and proficiency in Python (or a similar programming language such as Java or C#). Experience with AWS (Redshift, RDS, S3) and Google Cloud (BigQuery, Firebase) for managing cloud-based databases and analytics tools. Familiarity with data pipeline orchestration tools (dbt, Airflow, or similar). Strong knowledge of data warehousing concepts, ELT/ETL best practices, and dimensional modeling. Experience with version control systems (e.G., GitHub). Excellent communicator who can bridge technical depth with clear storytelling for non-technical stakeholders.


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