Data Engineer (Databricks) | PL

Accountabilities: The Data Engineer will be responsible for designing, developing, and maintaining data solutions that support business needs through scalable architectures and reliable processing workflows.

Develop and evolve data platforms focused on commercial credit and agribusiness solutions.

Design functional and data models aligned with business requirements and technical objectives.

Build, maintain, and optimize scalable and reliable data pipelines using modern processing technologies.

Perform data ingestion, transformation, validation, and availability processes while ensuring quality and performance.

Develop and maintain data architectures based on Data Lake and Data Lakehouse concepts.

Collaborate with multidisciplinary teams to understand requirements and deliver effective data solutions.

Apply best practices in data engineering, automation, and pipeline reliability.

Support continuous improvements in data processing efficiency and platform scalability.

Requirements:

The ideal candidate is a Data Engineer with experience building modern data platforms, distributed processing solutions, and cloud-based architectures. The role requires strong technical knowledge, analytical skills, and the ability to work with complex data environments.

Experience with Apache Spark for distributed data processing.

Experience with Apache Airflow for data pipeline orchestration.

Knowledge of Apache Kafka for real-time data processing and integrations.

Experience with dbt (Data Build Tool) for data transformation and modeling.

Experience working with SQL and NoSQL databases, including PostgreSQL, MongoDB, and Cassandra.

Experience with cloud data platforms such as Databricks, AWS Glue, and BigQuery.

Knowledge of implementing and maintaining Data Lake and Data Lakehouse architectures.

Ability to analyze business requirements and translate them into efficient data solutions.

Strong problem-solving skills and attention to data quality, reliability, and performance.

Benefits:

Opportunity to work on innovative data projects involving advanced technologies.

Exposure to modern cloud platforms and large-scale data architectures.

Professional growth in a technology-driven environment.

Opportunity to collaborate with multidisciplinary teams and contribute to impactful solutions.

Career development opportunities focused on continuous learning and emerging technologies.

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? 

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