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Data Engineer
2 weeks ago
- Design, develop, and maintain data pipelines and ETL processes to collect, transform, and integrate data from multiple sources.
- Manage and optimize Data Warehouse / Data Lake to ensure scalability, reliability, and high performance.
- Build and maintain data models and data architecture to support business intelligence, analytics, and data science use cases.
- Collaborate with Business Analysts, Data Scientists, and Software Engineers to deliver high-quality, reliable datasets.
- Develop tools for monitoring, logging, and data quality checks.
- Troubleshoot data-related issues and continuously improve system performance.
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Technology, or related field.
- 4–7 years of professional experience as a Data Engineer.
- Strong proficiency in SQL (advanced level) and experience with Relational Databases (e.g., MySQL, PostgreSQL, SQL Server).
- Hands-on experience with Big Data frameworks (e.g., Hadoop, Spark, Hive, Kafka).
- Practical knowledge of at least one Cloud Platform (AWS, GCP, or Azure), such as AWS Glue/Redshift/EMR, GCP BigQuery/Dataflow, Azure Synapse/Data Factory.
- Solid programming skills in Python, Java, or Scala.
- Deep understanding of ETL/ELT, Data Warehousing, and Data Modeling concepts.
- Familiarity with CI/CD, Git, Docker, Kubernetes is a plus.
- Strong analytical, problem-solving, and collaboration skills.
