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Data engineer (Azure Databricks)

Today 2026/09/03
Other Business Support Services
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Job description

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.
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 .
This job post has been translated by AI and may contain minor differences or errors.
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