Senior Data Engineer Con II
Allstate · Remote · United States · 10d ago
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
Job DescriptionAllstate's Data & Analytics Technology organization is seeking a Senior Data Engineer to lead the design, development, and operation of scalable, resilient, and high-performing data platforms that power enterprise analytics, reporting, AI, and advanced data products. This role will be responsible for building and optimizing batch and streaming data solutions using Apache Spark, Microsoft Fabric, and modern cloud-native data technologies.
As a Senior Data Engineer, you will play a critical role in designing and implementing Lakehouse architecture based on Medallion (Bronze, Silver, Gold) principles, ensuring that data is governed, trusted, and readily consumable across the enterprise. You will partner closely with analytics engineers, architects, data scientists, and product teams to transform complex data into business-ready information assets through effective data engineering, modeling, and governance practices.
The ideal candidate possesses deep experience in large-scale data processing, dimensional data modeling, and modern software engineering practices, including leveraging Agentic AI-assisted development tools to accelerate engineering productivity, code quality, testing, and operational excellence.
Design, build, andmaintainscalable batch and real-time data pipelines usingApache Spark, SQL, Python, and cloud-native data technologies.
Architect and implementMedallion Lakehouse data patterns (Bronze, Silver, Gold)to support enterprise analytics, reporting, operational intelligence, and AI use cases.
Develop andoptimizeETL/ELT pipelines that ingest, transform, standardize, and curate data from diverse enterprise source systems.
Design and implement robustDimensionalmodels, including fact and dimension tables, to support reporting, self-service analytics, and business intelligence solutions.
Build and manage data workloads withinMicrosoft Fabric,OneLake, and modern Lakehouse platforms.
Establish data quality, observability, and governance frameworks through automated validation, reconciliation, monitoring, and alerting capabilities.
OptimizeSpark workloads for performance, scalability, reliability, and cost efficiency across large and complex datasets.
Design solutions that effectively manage schema evolution, data lineage, metadata, and source-system changes.
Develop reusable frameworks, accelerators, and engineering standards that improve consistency anddeliveryvelocity across teams.
LeverageAgentic AI-assisted development capabilitiesto accelerate code generation, testing, documentation, troubleshooting, and engineering productivity while adhering to enterprise governance standards.
Implement CI/CD pipelines andDevSecOpspractices to enable automated testing, deployment, release management, and rollback strategies.
Lead technical design reviews and provide mentorship to junior and mid-level data engineers.
Collaborate with data architects, business stakeholders, analytics engineers, and data scientists to translate business requirements into scalable data solutions.
Partner with platform, security, privacy, and governance teams to ensure compliance with enterprise policies and regulatory requirements.
Drive continuous improvement across data engineering practices, architecture standards, and Agile delivery processes.
Required Qualifications
7+ years of experience as aData Engineer, building and supporting enterprise-scale data platforms and pipelines.
Strong hands-on experience withApache Sparkfor large-scale distributed data processing.
AdvancedproficiencyinPython,SQL, and modern data engineering development practices.
Experience designing and implementingLakehouse architecturesandMedallion Architecture patterns.
Strong understanding ofdimensional modeling, including star schemas, snowflake schemas, fact tables, dimension tables, and semantic data models.
Experience withMicrosoft Fabric,OneLake, Delta/Parquet formats, or comparable cloud analytics platforms.
Expertise indata integration, transformation, and optimization techniques for large-scale analytical workloads.
Experience implementing CI/CD pipelines, source control, Infrastructure as Code (IaC), and automated testing practices.
Familiarity with AI-powered engineering tools andAgentic AI-assisted software development practices.
Strong understanding of distributed computing, performance tuning, scalability, fault tolerance, and data reliability.
Excellent problem-solving, collaboration, communication, and stakeholder management skills.
Experience leading technical initiatives and mentoring engineering team members.
Preferred Qualifications
Experience with real-time and event-drivenarchitecturesusing Kafka, Event Streams, or similar technologies.
Experience designing and implementing enterprise data products withinMicrosoft Fabric.
Familiarity with Data Vault, Kimball, or other enterprise data modeling methodologies.
Experience supporting machine learning, generative AI, or advanced analytics workloads.
Knowledge of data governance, metadata management, master data management, and data quality frameworks.
Cloud certifications or data engineering certifications in Azure, Microsoft Fabric, Databricks, or related technologies.
Leadership Expectations
Serve as a technical leader and trusted advisor for data engineering best practices.
Champion modern data architecture patterns, reusable engineering standards, and automation-first approaches.
Drive adoption of AI-assisted engineering practices to improve developer productivity and solution quality.
Mentor and coach engineering team members while fostering a culture of innovation, ownership, and continuous learning.
Supervisory Responsibilities
This position does not have direct people management responsibilities but is expected to provide technical leadership, mentorship, and guidance across project teams and engineering initiatives.
Skills
Apache Spark, Data Engineering, Python (Programming Language), Structured Query Language (SQL)Compensation
Compensation offered for this role is 90,700.00 - 153,925.00 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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