AI Native Data Engineer

Palo It · PALO IT Mexico · posted Sep 8, 2026

Open to candidates in Mexico

More remote jobs open to candidates in Mexico

Full-timemidinsurance

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What this role actually asks for

Extracted by RemoteHunt

Must have

  • Design, build, and maintain scalable data pipelines
  • Integrate structured and unstructured data
  • Automate data ingestion, transformation, quality
  • Build modern data lakes and warehouses
  • Implement data quality, lineage, governance
  • Experience with Spark, databricks, dbt, Kafka
  • Strong Python and advanced SQL

Nice to have

  • Familiarity with event-driven architectures
  • Experience in financial or insurance sector
  • Azure Data Engineer or Fabric Data Engineer certifications
  • Experience with MLOps solutions

Tools and technologies

AWSGCPAzureSparkdbtKafkaAirflowSnowflakeBigQueryRedshiftGreat ExpectationsDeequOpenMetadataPower BILooker

Languages required

en

The full posting

Who We Are

Building the AI-first frontier enterprise.

We are a global technology consultancy with a trademarked, AI-first approach —Gen-e2™. It redefines how enterprises build digital products and transform their organizations with AI. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.

  • We are small enough to care locally, big enough to deliver globally ( 10 countries, 450+ experts from 50+ nationalities )

  • We are becoming an agentic organization, adopting the AI-native operating model we bring to our clients.

  • We are robust and resilient (100% independent, 0 debt, founded 2009)

  • We are AI-native professionals who invest in what we believe and work as a collective intelligence

  • We are positive, courageous and deliver at the leading edge.

Your 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.

  • 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, ERP).

  • Automate data ingestion, transformation, and quality processes using tools such as 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, etc.) 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.

Who You Are .

  • 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.

Nice to Have

  • Familiarity with event-driven architectures and microservices.

  • Previous experience in the financial or insurance sector.

  • Certifications such as Azure Data Engineer or Fabric Data Engineer.

  • Experience with MLOps solutions (Vertex AI, SageMaker, MLFlow).

AI-Native Engineering (Core Expectation)

  • Use Generative AI coding tools (e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for:

  • Code scaffolding and refactoring

  • Code generation and optimisation

  • Test-cases and documentation generation

  • Build applications through AI-driven development practices , including:

  • AI-assisted debugging and troubleshooting

  • Intelligent code completion and pattern recognition

  • Automated documentation generation

  • Apply prompt engineering best practices for reliable, repeatable engineering outcomes.

  • Validate GenAI output (determinism checks, guardrails, fallback logic).

More About PALO IT

Our clients include some of the world’s most successful companies. We collaborate with leading enterprises, next-generation businesses and frontier partners, shaping what comes next, helping them scale AI and solve complex business and technology challenges.

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

For more on our team culture and benefits, check out our careers page .

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