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Databricks Data Engineer
Job summary
A tech consulting firm is seeking a Databricks Data Engineer for a fully remote contract role. This position requires strong hands-on experience with Databricks, Spark, and SQL to build scalable data pipelines and optimize ETL processes. Responsibilities include ingesting and transforming data from diverse sources, developing reusable frameworks, and delivering insights via Power BI. Strong knowledge of data quality and hands-on experience with Azure CI/CD pipelines will be advantageous.
Qualifications
- Hands-on experience with Databricks, Spark, and Delta Lake required.
- Advanced SQL skills for data processing are essential.
- Experience integrating diverse data sources highly valued.
Responsibilities
- Build and optimize ETL/ELT pipelines in Databricks.
- Ingest, clean, and transform data from various sources.
- Develop reusable pipeline frameworks and validate data.
Skills
Tools
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.
- 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.
- 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.
- 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.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.