Data Engineer designing and optimizing scalable data pipelines and cloud architectures at Hartford. Collaborating with analytics and AI teams for data quality and feature deployment.
Responsibilities
Design, develop, and maintain scalable data pipelines and ETL/ELT processes for structured and unstructured data
Build and optimize cloud-based data architectures, data lakes, and data warehouses (preference for GCP)
Ingest data from diverse sources including APIs, databases, streaming platforms, and third-party systems
Ensure data quality, reliability, performance, and scalability across data platforms
Optimize data models for analytics, reporting, and machine learning use cases
Collaborate with analytics, data science, and AI teams to support feature engineering and model deployment
Implement monitoring, logging, and alerting to ensure pipeline health and performance
Apply best practices for security, data governance, privacy, and access controls
Document data pipelines, schemas, and architectural decisions to promote transparency and reusability
Requirements
Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent experience)
Strong programming experience in SQL and at least one of Python, Java, or Scala
Experience designing and building data pipelines and data platforms in a cloud environment
Solid understanding of data warehousing concepts, dimensional modeling, and data optimization
Experience working with large datasets and distributed data processing frameworks
Familiarity with CI/CD, version control (Git), and infrastructure-as-code concepts
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