Job Description
Team: IT
This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Engenheiro de Dados in Brazil.
This is a senior data engineering role focused on designing, building, and scaling modern data platforms to support advanced analytics, business intelligence, and AI-driven initiatives. You will work in a highly technical environment, leveraging cloud-native architectures and big data technologies to transform large and complex datasets into reliable, high-quality data products. The role involves hands-on development of data pipelines, real-time processing systems, and scalable data infrastructures. You will collaborate closely with analytics, engineering, and business teams to ensure data is structured, accessible, and ready for strategic decision-making. Operating in a remote-first setup, you will contribute to high-impact initiatives within a data-driven and innovation-focused organization. This position is ideal for someone who enjoys solving complex data challenges and working with modern distributed systems at scale.
Accountabilities:
- Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and process data from multiple sources into data lakes and data warehouses.
- Develop and optimize data architectures using relational and NoSQL databases, ensuring performance, scalability, and data integrity.
- Implement and manage big data processing solutions using distributed computing frameworks, with a strong focus on Databricks environments.
- Work with cloud platforms (AWS, Azure, or GCP) to deploy, automate, and maintain data infrastructure using modern DevOps and IaC practices.
- Build and support real-time and batch processing pipelines using technologies such as Spark, Delta Lake, and structured streaming.
- Collaborate with data analysts, data scientists, and business stakeholders to ensure data availability for dashboards, analytics, and AI/ML models.
- Contribute to the continuous improvement of data platforms, ensuring governance, quality, and scalability standards are met.
- Solid experience as a Data Engineer working with large-scale data systems and cloud-based architectures.
- Strong hands-on expertise in Databricks, Apache Spark, Delta Tables, Python, SQL, and Git.
- Experience designing and implementing ETL/ELT pipelines and data lake/lakehouse architectures.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
- Experience with distributed data processing, including Spark Structured Streaming and real-time data pipelines.
- Familiarity with Delta Sharing, MLflow, DABs (Databricks Asset Bundles), and DLT (Delta Live Tables).
- Experience with infrastructure automation and DevOps practices (CI/CD, IaC).
- Exposure to machine learning workflows and agent-based frameworks (e.g., LangChain or similar) is a plus.
- Experience in the financial sector is highly valued.
- Strong analytical mindset, problem-solving skills, and ability to work collaboratively in cross-functional teams.
- Databricks Professional Certification is strongly preferred.
- Competitive compensation aligned with senior data engineering roles.
- Remote-first work model with flexibility.
- Health and dental insurance coverage for employees and dependents.
- Wellness support including psychological consultations and nutrition assistance.
- Gympass access and wellness programs such as massage sessions.
- Life insurance coverage.
- Meal and food allowances.
- Education discounts and language learning partnerships.
- Transportation support options (voucher, shuttle, or parking assistance).
- Childcare assistance and additional family-oriented benefits.
- Birthday day-off and flexible perks for work-life balance.
Requirements:
Benefits:
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Date Posted
05/29/2026
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