✦ Luna Orbit — Data & Analytics

Staff Data Engineer - Hybrid

at Hartford Financial Services Group

📍 4 Locations Hybrid 💰 $125K – $188K USD / year Posted March 26, 2026
Salary $125K – $188K USD / year
Type Full-Time
Experience mid
Exp. Years Not specified
Education Not specified
Category Data & Analytics

This role involves designing and implementing cloud-based data pipelines to support enterprise analytics, focusing on data ingestion, transformation, and governance within a hybrid cloud environment.

  • Build data pipelines
  • Ensure data quality
  • Collaborate with data teams
  • Implement cloud solutions
  • Document technical processes

The technical environment includes AWS, Hadoop/EMR, Spark, Kafka, Snowflake, and Talend, with a focus on data engineering, cloud architecture, and big data methodologies.

The ideal candidate is a mid-level data engineer with experience in cloud-based data platforms, ETL processes, and big data technologies such as Hadoop, Spark, and Kafka. They should have strong Python and SQL skills and be familiar with data governance and cloud data solutions.

PythonSQLAWSData pipelinesData transformationCloud platformsELT solutionsData governance
HadoopEMRSparkKafkaSnowflakeTalendDevOpsData science algorithms
AWSHadoop/EMRSparkKafkaSnowflakeTalend
PythonSQLAWSHadoopEMRSparkKafkaSnowflakeTalendData pipelinesData transformationCloud platformsELTData governance
PythonSQLAWSAmazon Web ServicesHadoopEMRSparkKafkaSnowflakeTalendELTData pipelinesData transformationCloud-based data platformsDevOps practicesData governance
PartnershipCommunicationTechnical documentationProblem-solvingMentoringCollaborationSolution architectureResearchDesign thinking
Industry Insurance
Job Function Design and develop scalable data pipelines for enterprise data management
Role Subtype Data Engineer
Tech Domains Amazon Web Services, Hadoop, EMR, Spark, Kafka, Snowflake, Talend
Data EngineerAWSAmazon Web ServicesHadoopEMRSparkKafkaSnowflakeTalendData pipelinesData transformationCloud data platformsELTData governancePythonSQL

Lack of experience with AWS or cloud platforms, No experience with data pipelines or ETL, No programming skills in Python or SQL, Lack of understanding of data governance

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