Data Engineer; Remote

Data Engineer (Remote, US) page is loaded## Data Engineer (Remote, US) remote type:
Fully Remote locations: USA - IL (Remote) time type:
Full time posted on:
Posted Yesterday job requisition : R35408

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers' evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.
** Job Description
** Allstate's Risk Data Team is seeking a Data Engineer to help build the trusted data foundation that enables faster decisions, proactive risk management, and measurable improvements in control effectiveness. This role will focus on transforming fragmented risk and control data into reliable, accessible, and actionable information through scalable data pipelines, governed datasets, analytics-ready data products, and automation.

You will work closely with analytics engineers, product teams, risk partners, platform teams, and governance stakeholders to integrate data from internal platforms, vendor tools, and external sources. The role plays a critical part in reducing reliance on manual reporting and spreadsheets, improving confidence in risk data, and enabling dashboards, reporting, analytics, and future AI-based capabilities across the organization.###

Key Responsibilities
* Design, build, and maintain trusted risk data products and scalable batch and streaming data pipelines using cloud-native technologies.
* Integrate data from risk platforms, control systems, vendor tools, operational applications, and external sources into governed, analytics-ready datasets.
* Develop and optimize ETL/ELT workflows that automate data ingestion, transformation, validation, reconciliation, and delivery.
* Build and manage data processing workloads within modern data lake and lakehouse environments, including Microsoft Fabric and One Lake.
* Implement data quality, monitoring, lineage, and reconciliation processes to ensure data reliability, consistency, and accuracy.
* Create curated datasets and analytical outputs that support operational reporting, leadership dashboards, trend analysis, risk identification, and decision-making.
* Optimize data architectures, schemas, and processing patterns for scalability, performance, resilience, and cost efficiency.
* Develop reusable frameworks, engineering standards, CI/CD pipelines, automated testing, and operational monitoring to improve productivity and maintainability.
* Partner with analytics, product, risk, governance, security, and compliance stakeholders to establish data definitions, metrics, quality standards, and secure data access.
* Participate in Agile delivery activities including sprint planning, backlog refinement, design reviews, and continuous improvement initiatives.###

Required Qualifications
* 4+ years of experience as a Data Engineer or in a similar role building and supporting production-grade data pipelines and data products.
* Hands-on experience with Apache Spark for large-scale data processing and transformation.
* Strong proficiency in Python, SQL, and modern data engineering best practices.
* Experience developing ETL/ELT solutions within cloud-based data lake, lakehouse, or analytics platforms.
* Experience designing and optimizing analytical data models that support reporting, dashboards, operational insights, and advanced analytics.
* Strong understanding of data quality, validation, monitoring, reconciliation, and production support processes.
* Experience with CI/CD pipelines, version control, automated…