Remote Data Engineer: Build Trusted Risk Data Pipelines

Allstate; United States; Hybrid; USD 100,000 - 171,000; Full time

Benefits offered by this job

Tech setup including laptop, monitors,

Connectivity reimbursement for home Wi

Home internet requirements met

Job summary

Allstate’s Risk Data Team seeks a Data Engineer to transform fragmented risk data into reliable, accessible information through scalable pipelines and governed datasets. You will work with analytics engineers, product teams, risk partners, and governance stakeholders to enable dashboards, analytics, and AI-enabled capabilities.

Responsibilities include building batch and streaming data pipelines, integrating diverse data sources, and implementing data quality and CI/CD practices to ensure data

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.
• 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 testing, and infrastructure-as-code concepts.
• Demonstrated ability to troubleshoot complex data quality, performance, and integration issues across multiple data sources.
• Strong verbal and written communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
• Experience with Microsoft Fabric, OneLake, or similar modern analytics platforms preferred.

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 OneLake.
• 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.

Skills

Apache Spark

Python

SQL

ETL/ELT

Tools

Microsoft Fabric

OneLake

Job description

Allstate’s Risk Data Team seeks a Data Engineer to transform fragmented risk data into reliable, accessible information through scalable pipelines and governed datasets. You will work with analytics engineers, product teams, risk partners, and governance stakeholders to enable dashboards, analytics, and AI-enabled capabilities.

Responsibilities include building batch and streaming data pipelines, integrating diverse data sources, and implementing data quality and CI/CD practices to ensure data