AWS Spark Scala Data Engineer D&A Santander

Role & responsibilities

Data Engineer

Big Data, Spark, HDFS, Kafka, AWS, Azure, GCP, ETL, Hadoop, Hive etc.

Preferred candidate profile

Strong experience in programming languages such as Python, Java, or Scala for data manipulation and engineering tasks.

• Expertise in SQL and NoSQL databases
• Hands-on experience with big data technologies like Hadoop, Spark, Kafka, and Hive to handle large-scale data processing and real-time data streams.
• In-depth knowledge of data warehousing solutions such as Amazon Redshift, Google BigQuery, and Snowflake for building and managing data warehouses.
• Proficiency in designing, developing, and maintaining ETL (Extract, Transform, Load) processes using tools like Apache NiFi, Talend, or Informatica.

Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying, managing, and scaling data infrastructure and services.

• * Strong understanding of data modeling concepts and techniques to create efficient and scalable data models.
• Experience with version control systems such as Git for code management and collaboration.
• Knowledge of data governance, data quality standards, and data security practices to ensure compliance and protection of sensitive information