À propos
Key Responsibilities
Design, develop, and optimize highly scalable batch and near‑real‑time data pipelines supporting structured and unstructured data sources (XML, JSON, Parquet).
Lead the delivery of curated, analytics‑ready data products supporting reporting, advanced analytics, regulatory, and machine learning use cases.
Implement robust error handling, reconciliation, restartability, and performance optimization to ensure platform reliability and data integrity.
Partner with Data Governance team for metadata management, data lineage, data quality monitoring and data privacy controls.
Evaluate and apply AI‑assisted engineering tools to improve developer productivity, accelerate delivery, and enhance data solutions.
Provide technical mentorship while partnering with architects and stakeholders to influence and deliver a scalable, trusted AI and data pipelines grounded in best practices and reusable standards.
Required Qualifications & Experience
Authorized to work in the US without company sponsorship; the company will not support STEM OPT I‑983 endorsement for this position.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline.
5+ years of progressive experience in data engineering, with significant hands‑on expertise developing and deploying large‑scale data and analytics applications on cloud platforms such as AWS and Snowflake.
5+ years of hands‑on experience with Python and PySpark/Spark for data ingestion, transformation, and pipeline development.
Deep hands‑on experience with Snowflake, including SQL development, ELT design, performance optimization, and semi‑structured data handling.
Experience working with disparate data sources—structured, semi‑structured (Flat files, XML, JSON, Parquet) and unstructured data.
Experience with version control tools, CI/CD pipelines and DevOps tools like GitHub, Jenkins, Nexus and uDeploy.
Strong background in Data Profiling, Data Modeling and Data governance concepts.
Nice to Have
Certifications in AWS Data & Analytics Services, AI and Snowflake.
Experience using AI‑assisted development tools to improve productivity in SQL development, data pipeline creation, testing, and documentation.
Experience in the Insurance industry and policy administration data environments.
Experience with Informatica Data Management Cloud.
Work Schedule & Location This role will have a hybrid work schedule, with the expectation of working in an office (Columbus, OH; Chicago, IL; Hartford, CT; or Charlotte, NC) 3 days a week (Tuesday through Thursday).
Compensation The listed annualized base pay range is $125,760 - $188,640. Additional rewards may include short‑term or annual bonuses, long‑term incentives, and on‑the‑spot recognition.
Equal Opportunity Employer / Sex / Race / Color / Veterans / Disability / Sexual Orientation / Gender Identity or Expression / Religion / Age.
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Compétences linguistiques
- English
Avis aux utilisateurs
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