Databricks Data Engineer

GlobalSource IT; Betim; Teletrabalho; BRL 120.000 - 150.000; Tempo integral

Resumo da oferta

A leading IT company is seeking a Databricks Data Engineer to build and optimize data pipelines. This fully remote role involves ingesting and transforming data from multiple sources, requiring strong hands-on experience in Databricks, Spark, and SQL. The ideal candidate will develop reusable frameworks and deliver insights through Power BI dashboards. Join us to ensure data accuracy and quality in a fast-paced environment.

Qualificações

• Strong experience in Databricks (Spark, PySpark, Delta Lake).
• Advanced SQL for processing large-scale data.
• Ability to integrate data from various sources.

Responsabilidades

• Build and optimize ETL / ELT pipelines in Databricks.
• Ingest and transform data from diverse sources.
• Develop reusable pipeline frameworks.

Conhecimentos

Databricks

SQL

Spark

PySpark

Delta Lake

Power BI

Ferramentas

Azure

Airflow

Kafka

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.