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Lead Data Engineer Digital Engineering & Transformation
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- The ideal candidate must be hands-on and will have a strong background in data engineering, with proven experience in developing and deploying large-scale data solutions in a cloud environment, must be metrics-focused and obsessed with Cloud native and DevOps technologies.
- In this role, you will have the opportunity to make a lasting impact on the digital transformation journey, drive customer-centric innovation, and the ideal candidate will have a background of running transformation projects in similar disruptive industries such as Digital Payments or Fintech.
- Minimum of 5 years' experience in data lake / lakehouse, distributed systems and data, data virtualization, microservices, and machine learning.
- Minimum of 5 years of hands-on skills in Python, Apache Spark, Hive, Cassandra, Snowflake, Elastic, Lucene, DataBricks, Hadoop, Redshift, Scala, Java, or other relevant technologies in data engineering.
- Minimum of 5 years' experience building containerized applications and deploying them to public or private clouds, such as Amazon Web Services (AWS), Microsoft Azure, or similar providers, end-to-end SaaS applications, and highly scalable software products.
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