Databricks Data Engineer

Globalsource It; Teletrabalho; BRL 120.000 - 160.000; Tempo integral

Resumo da oferta

A technology consulting firm is seeking a Databricks Data Engineer for a fully remote contract. This role focuses on building scalable data pipelines using Databricks with Spark, PySpark, and SQL. Responsibilities include ingesting data from various sources, optimizing ETL pipelines, and creating visualizations through Power BI. The ideal candidate will have strong experience in Databricks, SQL, and data integration. Join us to leverage your skills in a collaborative remote environment.

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.

Responsabilidades

• Build and optimize ETL / ELT pipelines in Databricks.
• Ingest, clean, and transform data from diverse sources.
• Develop reusable pipeline frameworks and performance-tuned transformations.

Conhecimentos

Databricks experience (Spark, PySpark, Delta Lake)

Advanced SQL

Data integration from structured and unstructured sources

Distributed computing knowledge

Power BI

CI/CD pipelines in Azure

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.