AI Native Data Engineer

About the role

As an AI Native Data Engineer for a leading insurance company, you will design resilient and secure data solutions that turn 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 tools like Apache Spark, dbt, Kafka, and Airflow.
• Build and maintain modern data lakes and warehouses (Snowflake, BigQuery, Redshift).
• Implement data quality, lineage, and governance validations (Great Expectations, Deequ, OpenMetadata).
• Ensure compliance with data regulations (GDPR, SOC2) and internal security policies.
• Design optimized datasets to enable machine‑learning models, predictive analytics, and dashboards (Power BI, Looker, Tableau).
• Collaborate with data scientists, architects, and business stakeholders to democratize access to trusted data.
• Document data architectures, pipelines, transformation standards, and lineage.

Required profile

• Experience with modern data processing frameworks: Spark, Databricks, dbt, Kafka, Apache Beam.
• Strong command of Python and advanced SQL.
• Hands‑on experience with Azure cloud platforms (Data Factory, Synapse).
• Knowledge of modern Data Lake / Data Warehouse design (Snowflake, Redshift, BigQuery).
• Familiarity with DataOps, testing, and CI/CD practices in data pipelines.
• Experience with workflow orchestration systems such as Airflow or Dagster.
• Understanding of data quality and governance frameworks: Great Expectations, Deequ, DataHub, OpenLineage.
• Knowledge of streaming technologies: Kafka, Pub/Sub, Kinesis.
• Upper‑intermediate English level (B2 or higher) for global collaboration.

Required skills

• Apache Spark
• Databricks
• dbt
• Kafka
• Apache Beam
• Python
• SQL
• Azure Data Factory
• Azure Synapse
• Snowflake
• Redshift
• BigQuery
• Airflow
• Dagster
• Great Expectations
• Deequ
• DataHub
• OpenLineage
• Pub/Sub
• Kinesis
• Power BI
• Looker
• Tableau

What we offer

• Stimulating working environments
• Unique career path
• International mobility
• Internal R&D projects (including Gen‑e2™)
• Knowledge sharing
• Personalized training via PALO IT Academy
• Entrepreneurship & intrapreneurship