Senior Specialist - Data Engineering

About the role

As a Senior Data Engineer you will design, develop and maintain scalable data pipelines and storage solutions, ensuring data is reliable, accessible and aligned with business goals. You will work closely with cross‑functional teams including data science, marketing and customer success to support analytics and machine‑learning initiatives.

Key responsibilities

• Design, develop and operate ETL pipelines using Apache Spark, Kafka, Airflow, Apache Beam and Hadoop/Spark on Google Cloud Platform.
• Deploy data processing jobs on DataFlow, DataProc, Data Fusion and Cloud Composer.
• Implement and optimise data warehouses (BigQuery, Amazon Redshift) and data lakes (AWS S3, Azure Data Lake Storage) and NoSQL stores such as MongoDB and Cassandra.
• Collaborate with data architects to model dimensional schemas (star, snowflake) and support advanced analytics and ML model training.
• Configure GCP services, perform data quality checks, monitoring and automation of repetitive tasks.
• Troubleshoot data issues and contribute to continuous improvement of data platforms.

Required profile

• Bachelor’s degree in Computer Science, IT or related field; Master’s degree is a plus.
• Proven experience as a data engineer or similar role, preferably on Google Cloud Platform.
• Strong analytical skills, attention to detail and ability to work in a fast‑paced environment.
• Excellent communication and teamwork abilities.

Required skills

• Python, Java, Scala programming.
• SQL and NoSQL databases (MongoDB, Cassandra).
• Apache Spark, Apache Kafka, Apache Airflow, Apache Beam.
• Google Cloud Platform services, especially BigQuery.
• Data warehousing tools (Amazon Redshift, Google BigQuery) and data lake storage (AWS S3, Azure Data Lake Storage).
• Data modelling, ETL processes and dimensional modeling techniques.