What are the responsibilities and job description for the Databricks Data Engineer | Senior position at Jobgether?
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Databricks Data Engineer | Senior based in Brazil.
As a Senior Data Engineer, you will design and implement scalable data solutions that connect business needs with modern technology.
You will work across Data Lake and Data Lakehouse architectures, building reliable batch and streaming pipelines.
The role combines hands-on engineering with strategic thinking around data architecture and platform evolution.
You will help ensure data quality, governance, security, and performance across complex environments.
Close collaboration with Data and Business teams will be essential to turn data into actionable insights and better decisions.
You will also contribute to defining data strategies and mentor other data engineering professionals.
This is an opportunity to work with modern cloud and data technologies in a remote, innovation-driven environment.
- Define and implement Data Engineering solutions that effectively connect business requirements with technology capabilities.
- Design, build, and evolve scalable data architectures, including Data Lake and Data Lakehouse environments.
- Develop and manage robust batch and streaming data pipelines designed for scalability, reliability, and performance.
- Assess and improve processes for data collection, organization, transformation, and availability.
- Ensure data quality, governance, security, and performance throughout the data lifecycle.
- Partner closely with Data and Business teams to support data-driven decision-making and strategic initiatives.
- Help define data strategies and architectural approaches aligned with business objectives.
- Share technical expertise and mentor other Data Engineering professionals, supporting knowledge development across the team.
Requirements
- Solid professional experience in Data Engineering and data architecture.
- Advanced knowledge of Azure Data Factory and Databricks.
- Hands-on experience with Apache Spark and distributed data processing.
- Proven experience building and maintaining both batch and streaming data pipelines.
- Knowledge of orchestration technologies such as Airflow.
- Familiarity with Kafka and dbt.
- Experience working with both SQL and NoSQL databases, including technologies such as PostgreSQL, MongoDB, and Cassandra.
- Knowledge of cloud data platforms and services across AWS and GCP.
- Practical experience with Data Lake and Data Lakehouse architectures.
- Understanding of data governance, quality, and security practices.
- Strong analytical and problem-solving abilities, with the communication skills needed to collaborate effectively with technical and business stakeholders.
- Ability and willingness to mentor other engineers and contribute to technical decision-making.
Benefits
- 100% remote work model.
- Opportunity to work with modern Data Engineering, cloud, and AI-related technologies.
- Exposure to large-scale data architecture and complex engineering challenges.
- Collaborative environment with Data and Business professionals.
- Opportunities for technical development, knowledge sharing, and career growth.
- Opportunity to mentor peers and contribute to architectural and strategic data decisions.
- Remote work flexibility and access to a broader, borderless technology environment.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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