Design and implement scalable, high-performing data pipelines and optimize our data architecture.
Build and deploy cloud-native solutions leveraging Azure Data Services, Databricks and other Big Data technologies.
Collaborate across teams to understand and support their data needs while ensuring the data architecture supports ongoing and future initiatives.
Apply CI/CD practices in Data Analytics projects to streamline development and deployment processes.
Continuously optimize performance, scalability, and security in our data systems.

4+ years of experience in data engineering, software development, or related fields, with expertise in ingesting and processing large datasets.
Hands-on experience in Azure or other public cloud platforms, including working knowledge of services like Databricks or Apache Spark.
Skilled in Big Data Technologies (e.g., Kafka, Flink) and SQL for analytics.
Proficient in at least one programming language (e.g., Python, Scala, Java).
Motivated to work in an innovative environment, learning and applying best practices for cloud-native systems and distributed architecture.

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and external trainings.

Data Engineer – DataOps

Key skills