Databricks Data Engineer

GlobalSource IT; Teletrabalho; BRL 120.000 - 160.000; Tempo integral

Resumo da oferta

A tech services company is seeking a Databricks Data Engineer to build scalable data pipelines fully remote. Responsibilities include optimizing ETL processes, ingesting data from various sources, and designing datasets for analytics. Ideal candidates will have strong Databricks experience and advanced SQL knowledge. This role offers an opportunity to implement best practices in data transformation and visualization, along with a focus on performance tuning and data accuracy.

Qualificações

• Strong hands‑on Databricks experience (Spark, PySpark, Delta Lake).
• Advanced SQL for large‑scale data processing.
• Experience integrating data from multiple structured and unstructured sources.
• Solid understanding of distributed computing and performance tuning.

Responsabilidades

• Build and optimize ETL / ELT pipelines in Databricks.
• Ingest, clean, and transform data from diverse sources.
• Develop reusable pipeline frameworks and data validation logic.
• Design datasets and deliver insights through Power BI.

Conhecimentos

Databricks experience

SQL

Data integration

Distributed computing

Power BI

CI/CD pipelines

Descrição da oferta de emprego

Databricks Data Engineer

Fully Remote Contract

We’re looking for a hands‑on Databricks Data Engineer with strong experience building scalable data pipelines using Spark, PySpark, SQL, and Delta Lake. This role focuses on ingesting data from multiple sources, transforming it for analytics, and publishing high‑quality datasets and visualizations.

Responsibilities

• Build and optimize ETL / ELT pipelines in Databricks using PySpark, Spark SQL, and Delta Lake.
• Ingest, clean, and transform data from diverse sources (APIs, SQL databases, cloud storage, SAP / legacy systems, streaming).
• Develop reusable pipeline frameworks, data validation logic, and performance‑tuned transformations.
• Design curated datasets and deliver insights through Power BI dashboards.
• Implement best practices for lakehouse development, orchestration, and version control.
• Troubleshoot pipeline performance issues and ensure data accuracy, reliability, and quality.

Required Skills

• Strong hands‑on Databricks experience (Spark, PySpark, Delta Lake).
• Advanced SQL for large‑scale data processing.
• Experience integrating data from multiple structured and unstructured sources.
• Solid understanding of distributed computing, performance tuning, and debugging Spark jobs.
• Power BI (reports, models, DAX preferred).
• Experience with CI / CD pipelines in an Azure environment

Nice to Have

• Experience with data quality frameworks, Lakehouse monitoring, or DQX
• Knowledge of Airflow, ADF, IoT, Kafka or other tools is a plus
• Experience with SAP data is a plus.