Data Engineer
New
P
ParetoHealthHealthcare
RemoteFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3+ years of experience in data engineering or software engineering; 2+ years of hands-on experience with AWS data services.
- Required Skills
- AWSPythonSQLETLTypeScriptAWS Lambda
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
- 3+ years of experience in data engineering or software engineering roles focused on data pipelines and analytics platforms.
- 2+ years of hands‑on experience with AWS data services in a production environment (e.g., Lambda, Glue, Athena, S3).
- Strong experience with AWS serverless services such as Step Functions.
- Proficiency in Python and TypeScript for building ETL/ELT jobs and reusable libraries.
- Solid understanding of data modeling principles including dimensional, normalized, wide-table, and event-driven designs.
- Experience designing and operating data pipelines at scale for batch and near-real-time ingestion.
- Familiarity with SQL and query optimization in columnar data stores.
- Knowledge of data quality, governance, and security practices for sensitive data.
- Hands‑on experience with Infrastructure as Code, preferably AWS CDK.
Responsibilities
- Design, implement, and maintain scalable, fully serverless data pipelines on AWS using Lambda, Glue, Athena, Step Functions, and S3.
- Build and evolve data models and schemas for performance, analytics, and AI engineering.
- Develop ETL/ELT workflows to ingest, cleanse, transform, and load data from various sources.
- Partner with Product, Underwriting, Analytics, and AI stakeholders to define data requirements.
- Implement data quality controls, monitoring, and alerting for critical datasets.
- Optimize serverless workloads for cost, performance, and scalability.
- Contribute to best practices including version control, CI/CD, and Infrastructure as Code using AWS CDK.
- Design and maintain feature stores and reusable data assets.
- Troubleshoot pipeline issues and provide ongoing production support.
- Document data models, pipelines, and data contracts.
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