Data Engineer

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

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 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.

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 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.

Essential Qualifications

• Experience working with risk, controls, compliance, audit, governance, or regulatory data domains.
• Experience building real‑time, near real-time, or event‑driven data processing solutions.
• Familiarity with data governance, metadata management, data lineage, access controls, and enterprise data quality frameworks.
• Experience with orchestration and workflow management tools for data pipelines.
• Experience supporting operational reporting, executive dashboards, trend analysis, advanced analytics, or machine learning initiatives.
• Interest in building governed, scalable datasets that support AI and data‑driven products.

Skills

Apache Spark, Data Engineering, Data ETL, Python (Programming Language), Software Development, Structured Query Language (SQL)

Compensation

Compensation offered for this role is 100,000.00 - 170,500.00 annually and is based on experience and qualifications. The candidate(s) offered this position will be required to submit to a background investigation.

Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.

Allstate generally does not sponsor individuals for employment-based visas for this position.

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Benefits

• Allstate provides a comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse.
• Employees eligible to work from home also receive a monthly connectivity reimbursement to help offset internet costs.
• Reliable internet is required, with minimum speeds of 50 MB download and 5 MB upload.
• When working from home, you must have a dedicated, private workspace free from distractions, along with appropriate desk and seating.

To help create a more personal and engaging experience, we ask that you join with your camera on if your interview is virtual.

If you require any accommodations or have questions ahead of your interview please reach out to your recruiter.

Note: Internal candidates are only asked to join on video; a Valid Photo Identification is not needed for the interview.

Allstaters are dedicated to serving clients, customers, and communities, which allows employees to find meaning and value in their work.

Allstate offers an environment that fosters innovative thinking where you’ll be able to explore your ideas and feel proud of the work you do.

Allstate helps protect nearly 16 million households with auto, home, life, and retirement products.

We want every professional connected to Allstate to be committed to giving our customers the best and that means finding the best talent.