
10,000+ employees
Founded 1931
💼 Consulting
📦 Logistics
🛡️ Insurance
💰 Post-IPO Equity on 2014-01
Consulting • Logistics • Insurance
Allstate is an industry leader in providing insurance solutions, focusing on home, auto, device, and identity protection. With a commitment to customer well-being, Allstate aims to instill peace of mind and financial security for its customers. The company also emphasizes community impact and sustainability through various initiatives, showcasing their dedication to social responsibility and positive change.
🕒 July 23
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10,000+ employees
Founded 1931
💼 Consulting
📦 Logistics
🛡️ Insurance
💰 Post-IPO Equity on 2014-01
Consulting • Logistics • Insurance
Allstate is an industry leader in providing insurance solutions, focusing on home, auto, device, and identity protection. With a commitment to customer well-being, Allstate aims to instill peace of mind and financial security for its customers. The company also emphasizes community impact and sustainability through various initiatives, showcasing their dedication to social responsibility and positive change.
• Design, build, and maintain scalable batch and streaming data pipelines using Apache Spark and cloud‑native data technologies • Develop and optimize ETL/ELT workflows to ingest, transform, and curate data from diverse source systems into analytics‑ready datasets • Implement data modeling and transformation logic to support reporting, dashboards, and downstream analytical and machine learning workloads • Build and manage data processing workloads within modern lakehouse platforms, including Microsoft Fabric / OneLake (preferred) • Ensure data quality, reliability, and consistency by implementing validation checks, monitoring, and reconciliation processes • Optimize Spark jobs for performance, cost efficiency, and scalability across large and complex datasets • Manage and evolve data schemas while handling schema drift and upstream source changes • Develop reusable frameworks, libraries, and standardized patterns to improve data engineering productivity and consistency • Implement CI/CD pipelines for data workloads to enable automated testing, deployment, and rollback • Monitor data pipelines and jobs, troubleshoot failures, and resolve performance or data quality issues • Partner with analytics engineers, BI developers, and data scientists to understand data requirements and deliver curated datasets • Collaborate with platform, security, and governance teams to ensure data security, compliance, and proper access controls • Contribute to Agile delivery processes, including sprint planning, design reviews, and continuous improvement initiatives
• 4+ years of experience in data engineering or equivalent role (preferred) • Strong experience as a Data Engineer building and operating production data pipelines • Hands‑on experience with Apache Spark for large‑scale data processing • Proficiency in Python, SQL, and data transformation best practices • Experience with cloud‑based data platforms and storage (e.g., Data Lakes, Lakehouse architectures) • Familiarity with Microsoft Fabric, OneLake, or similar analytics platforms (strong plus) • Experience designing and optimizing data models for analytical workloads • Understanding of distributed data processing concepts, performance tuning, and fault tolerance • Experience with CI/CD, version control, and infrastructure‑as‑code concepts • Strong problem‑solving skills and ability to troubleshoot complex data issues • Excellent communication skills and ability to collaborate across technical and non‑technical teams
• Comprehensive technology setup including laptop, monitors, headset, keyboard, and mouse • Monthly connectivity reimbursement to help offset internet costs • 401(k) matching • Health insurance plans • Employee assistance program • Paid time off and holiday pay
Apply Now🕒 July 23
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