Senior Data Engineer

Allstate

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
IL
Salary
$80,000–$136,625 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $163k
This role $108k
$66k $213k
below market most similar roles pay here above market

This role pays less than 91% of similar roles. Most pay $126,800–$199,175 — the blue band above. At the midpoint, this role pays about $108k versus about $163k for comparable roles.

Based on 240 similar postings.

Employer

About Allstate

The Allstate Corporation is one of the largest publicly held personal lines insurers in the US, widely recognized for its "You're In Good Hands With Allstate®" slogan.

Allstate currently has 55 open roles on FindRole.

Listed pay typically runs $100,000–$170,500 across 53 roles with salary data.

Most-posted roles

View all roles at Allstate

At a glance

TL;DR · Senior Data Engineer

The Senior Data Engineer will join the team to design, build, and own scalable data products and pipelines using Microsoft Fabric and modern data engineering practices. This role involves developing high-quality data solutions, building reusable ingestion and transformation patterns, and integrating data from diverse sources like APIs, databases, and event streams. The engineer will be responsible for the end-to-end lifecycle of data products, ensuring reliability, performance, and governance for digital products and analytics. Key technologies include PySpark, Python, SQL, NoSQL, Apache Spark, Kafka, Flink, dbt, and Docker. Candidates must demonstrate proficiency in data modeling, CI/CD, and containerization. The work focuses on creating unified views of business operations and optimizing workflows for cost efficiency and operational resilience within a product-centric engineering environment.

What does a Data Engineer earn?

Median $160500 from 198 postings across 59 companies.

See salary data

What you'll do

  • Design, build, and manage scalable data pipelines and processing systems using Microsoft Fabric.
  • Develop 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 to create unified, consistent views of business operations.
  • 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 to ensure transparency and maintainability.

What we're looking for

  • Strong proficiency in developing scalable data pipelines using PySpark and Python.
  • Hands-on experience with Apache Spark, Kafka, Flink, dbt, or equivalent technologies.
  • Strong knowledge of SQL, NoSQL databases, data modeling, and data architecture principles.
  • 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.
  • Experience with cloud data services (Azure, AWS) and familiarity with CI/CD pipelines (preferred).

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