Jobs / United States / Allstate Insurance Company
Data Engineer (Remote, US)
Allstate Insurance Company · 🇺🇸 USA - IL (Remote) · Remote
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. USCIS also records 25 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- 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. 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 roles1 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).
- Confirmed live todayWhen a source last listed this job as open.
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.
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Sponsor Radar — Allstate Insurance Company
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. USCIS also records 25 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Allstate Insurance Company →
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 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