Data Engineer – AI‑First Consultancy

About the role

As a Data Engineer for a leading insurance company, you will play a key role in building a data‑driven decision‑making culture. You will design resilient and secure solutions that transform raw data into strategic insights for underwriting, risk management, fraud prevention, and customer experience.

Key responsibilities

• Design, build, and maintain scalable and secure data pipelines in cloud environments (AWS, GCP, or Azure).
• Integrate large volumes of structured and unstructured data from core insurance systems such as policies, claims, CRM, and ERP.
• Automate data ingestion, transformation, and quality processes using Apache Spark, dbt, Kafka, and Airflow.
• Build and maintain modern data lakes and warehouses like Snowflake, BigQuery, and Redshift.
• Implement data quality, lineage, and governance validations with tools such as Great Expectations and OpenMetadata.

Required profile

• Strong command of Python and advanced SQL.
• Hands‑on experience with Azure cloud platforms (Data Factory, Synapse) and other major clouds.
• Experience with modern data processing frameworks such as Spark, Databricks, dbt, Kafka, and Apache Beam.
• Familiarity with DataOps, testing, and CI/CD practices for data pipelines.
• Upper‑intermediate English level (B2 or higher) for global collaboration.

Required skills

• Python
• SQL
• Apache Spark / Databricks
• dbt
• Kafka
• Apache Beam
• Azure Data Factory & Synapse
• Snowflake, Amazon Redshift, Google BigQuery
• Airflow (or Dagster)
• Great Expectations, Deequ, DataHub, OpenLineage

What we offer

• Stimulating working environment with a unique career path.
• International mobility and internal R&D projects, including the Gen‑e2™ AI platform.
• Personalized training through the PALO IT Academy and knowledge‑sharing initiatives.
• Opportunities for entrepreneurship and intrapreneurship.