✦ Luna Orbit — Data & Analytics

Director, Data Engineering

at Travelers

📍 CT - Hartford Hybrid 💰 $139K – $230K USD / year Posted March 13, 2026
Salary $139K – $230K USD / year
Type Full-Time
Experience lead
Exp. Years Not specified
Education Bachelor's Degree in STEM related field or equivalent
Category Data & Analytics

This role leads the data engineering team focused on building data pipelines and supporting AI/ML initiatives within the insurance enterprise, leveraging cloud platforms and modern data technologies.

  • Lead data pipeline development
  • Support AI/ML initiatives
  • Manage cloud data services
  • Mentor data engineers
  • Ensure scalable, secure data solutions

The position involves designing and managing data pipelines, utilizing cloud-native data services, and supporting analytics and AI/ML projects with tools like Spark, Kafka, Airflow, and dbt.

The ideal candidate is a senior data engineering leader with expertise in cloud platforms (AWS, Azure, GCP), data pipeline development, and AI/ML support, capable of leading analytics transformation and mentoring teams.

Data pipelinesCloud platforms (AWSAzureGCP)PythonPySparkSQLCI/CDVersion controlInfrastructure-as-code
Artificial IntelligenceMachine LearningBusiness intelligenceData strategiesEnterprise architecture
AWSAzureGCPSparkKafkaAirflowdbt
Data pipelinesArtificial IntelligenceMachine LearningBusiness intelligenceCloud platformsAWSAzureGCPSparkKafkaAirflowdbtPythonPySparkSQLCI/CDVersion controlInfrastructure-as-code
Data pipelinesArtificial IntelligenceMachine LearningBusiness intelligenceCloud platformsAWSAzureGCPCloud-native data servicesSparkKafkaAirflowdbtPythonPySparkSQLCI/CDVersion controlInfrastructure-as-code
LeadershipCommunicationTeam managementStrategic thinkingProblem-solving
Industry Insurance
Job Function Lead data engineering efforts to support enterprise analytics and AI/ML projects
Data pipelinesArtificial IntelligenceMachine LearningBusiness intelligenceCloud platformsAWSAzureGCPSparkKafkaAirflowdbtPythonPySparkSQLCI/CDVersion controlInfrastructure-as-code

Lack of experience with cloud platforms (AWS, Azure, GCP), No experience with data pipeline tools, Unwilling to work in a hybrid environment

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