Data engineer (Databricks)

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks.
• Build and optimize data workflows using Apache Spark (PySpark/Scala).
• Implement data ingestion from multiple sources (APIs, databases, streaming platforms).
• Develop and manage data lakes and lakehouse architectures.
• Work with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
• Optimize performance of queries and large-scale data processing jobs.
• Ensure data quality, governance, and security best practices.
• Collaborate with data scientists, analysts, and business stakeholders to deliver data solutions.
• Implement CI/CD pipelines and version control for data engineering workflows.

Requirements

• 5+ years of experience in data engineering or big data development.
• Strong hands-on experience with Databricks and Apache Spark (PySpark preferred).
• Proficiency in Python, SQL, and optionally Scala.
• Experience with data modeling, data warehousing, and ETL design.
• Hands-on experience with cloud platforms (AWS/Azure/GCP).
• Familiarity with tools like Airflow, Kafka, Delta Lake.
• Strong understanding of distributed computing and big data architecture.