Jobs / United States / Allstate Insurance Company

Allstate Insurance Company

Senior Data Engineer

USA - IL (Remote); 51 Locations · Remote · US only Posted today

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Skills this job asks for

Data engineeringCI/CDComplianceSparkPythonKafkadbtSQLDockerKubernetes

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Where you can work from

United States only

Based on the listing's location: USA - IL (Remote); 51 Locations.

The company's headquarters is not the same as where you may work from. Visa sponsorship only matters if you would relocate; see below.

Visa sponsorship, if you would relocate

Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 38 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Allstate Insurance Company paid sponsored hires in similar roles1 certified filing for “Applied Machine Learning Engineer Senior Expert” (Data Scientists) in CA: $193k–$193k, median $193k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 38 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Allstate Insurance Company paid sponsored hires in similar roles
1 certified filing for “Applied Machine Learning Engineer Senior Expert” (Data Scientists) in CA: $193k–$193k, median $193k. Most were filed at wage level II (100%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

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 e

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