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
Design, build, and own scalable data products and pipelines using Microsoft Fabric and modern data engineering practices, ensuring reliability, performance, governance, and effective delivery of trusted data for digital products and analytics.
As a Senior Data Engineer, you will design, build, and support high-quality data solutions and pipelines using modern engineering practices and tools. In this role, you will partner closely with product managers, software engineers, and data analysts to deliver scalable, reliable data capabilities that power digital products and business insights. You will be accountable for the end‑to‑end lifecycle of your data products, from design and implementation through production support, data quality, and performance against key metrics.
Key Responsibilities:
Design, Build & Manage Data Solutions
Design, develop, and enhance scalable data pipelines and data processing systems.
Build reusable ingestion, transformation, and storage patterns to support product and analytical needs.
Integrate data from diverse sources including APIs, databases, event streams, and third‑party systems.
Implement data models and schemas that create unified, consistent views of business operations.
Engineering Excellence
Apply modern engineering practices, including version control, testing, CI/CD, and automated deployments.
Ensure data quality, integrity, and reliability through validation, monitoring, and observability tools.
Optimize data workflows for performance, cost efficiency, and operational resilience.
Document data flows, lineage, and technical components in support of transparency and maintainability.
Product Collaboration & Delivery
Collaborate closely with product managers, engineers, and analysts to understand data requirements.
Participate in iteration planning, ensuring shared understanding of backlog items and technical needs.
Engage in daily standups, retrospectives, and product ceremonies as an active member of the team.
Governance, Standards & Continuous Improvement
Contribute to data governance practices such as metadata management and data lineage.
Ensure compliance with data privacy, security, and regulatory requirements.
Evaluate new technologies, frameworks, and patterns to improve data infrastructure and engineering capabilities.
Share knowledge and mentor less experienced engineers, contributing to team growth and best practices.
Core Skills
Strong proficiency in developing scalable data pipelines using PySpark and Python.
Hands-on experience with modern data engineering frameworks and tools, including Apache Spark, Kafka, Flink, dbt, or equivalent technologies.
Strong knowledge of SQL, NoSQL databases, data modeling, and data architecture principles.
Demonstrated ability to optimize SQL queries, data pipelines, and storage for performance, scalability, and cost efficiency.
Experience designing and developing batch and/or real-time streaming data solutions.
Hands-on experience with Microsoft Fabric Notebooks for developing, debugging, testing, and operationalizing data engineering workflows.
Experience with containerization and orchestration technologies, such as Docker and Kubernetes.
Experience implementing monitoring and observability solutions, with Datadog experience preferred.
Ability to work effectively in collaborative, iterative, and product-centric engineering environments.
Strong communication, analytical, troubleshooting, and problem-solving skills
Preferred Skills
Experience with cloud data services (Azure, AWS).
Hands‑on experience with…