This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Engenheiro de Dados Sênior based in Brazil.
This senior data engineering role sits at the center of large-scale, mission-critical data environments supporting highly complex industries such as financial services.
You will be responsible for designing, building, and evolving robust and scalable data pipelines in cloud-native architectures.
The role requires deep expertise in Databricks and AWS, ensuring high performance, governance, and reliability across data workflows.
You will work extensively with distributed processing frameworks such as Apache Spark, supporting both batch and streaming use cases.
Your work will directly impact data availability, quality, and strategic decision-making across multiple business domains.
This is a highly technical and collaborative environment where engineering excellence and data governance go hand in hand.
You will also contribute to modern data architecture design and integration across multiple enterprise systems.
Accountabilities:
- Design, build, and maintain scalable and high-performance data pipelines in cloud environments, ensuring reliability and governance across the full data lifecycle.
- Develop and optimize data processing workflows using Databricks, including Unity Catalog, Delta Lake, Workflows, Jobs, DLT, and SQL-based transformations.
- Implement batch and streaming data solutions using Apache Spark and Python notebooks for ingestion, transformation, and analytics.
- Integrate and manage data from multiple sources, ensuring consistency, quality, and alignment with enterprise data architecture standards.
- Work within AWS-based environments, ensuring secure, scalable, and high-availability data processing solutions.
- Design and support ETL/ELT processes and dimensional and relational data models for analytical and operational use cases.
- Collaborate with cross-functional teams to define data requirements and ensure delivery of high-impact data solutions.
Requirements:
- 7+ years of experience in data engineering or related roles within complex, enterprise-grade environments, preferably financial or highly regulated industries.
- Strong hands-on experience with Databricks ecosystem and its core components (Unity Catalog, Delta Lake, Jobs, Workflows, DLT, SQL Editor).
- Advanced knowledge of Apache Spark for both batch and streaming processing, with strong proficiency in Python.
- Solid experience working with AWS cloud services and distributed data architectures.
- Strong understanding of ETL/ELT processes, data modeling (relational and dimensional), and data quality best practices.
- Experience integrating with relational databases such as Db2 and SQL Server via JDBC or similar connectors.
- Proven ability to design and operate scalable, secure, and high-performance data platforms.
- Strong communication skills and ability to collaborate in agile, cross-functional environments.
- Differential: experience with real-time replication, data governance, Data Lakes, Scala, R, SAS, and MPP databases such as Netezza or Redshift.
Benefits:
- CLT employment contract
- Subsidized health insurance for employees
- Option to include dependents in health and dental plans
- Dental assistance (optional)
- Meal or food allowance
- Optional transportation voucher
- Emotional, legal, financial, and social support program
- Gympass / Wellhub access to nationwide fitness network
- Discounted dependent inclusion in wellness plan
- Access to Udemy learning platform
- Partnerships with major consumer brands
- SESC benefits for employees and dependents
- Education and language course discounts
- Group life insurance