[Hiring] Managing Engineer, Data Engineering @Allstate

Role Description

We are seeking Two Managing Engineers, Data Engineering to lead the design, development, and delivery of scalable data solutions that support digital products, analytics, and business decision-making. Both opportunities combine hands-on engineering with technical leadership, team development, and delivery responsibility. You will partner with Product Managers, Software Engineers, Data Analysts, Architects, and business stakeholders to deliver reliable, secure, and high-performing data products.

Key Responsibilities

• People and Engineering Leadership
  • Lead, mentor, and coach Data Engineers while supporting their technical and professional development.
  • Promote a culture of collaboration, accountability, knowledge sharing, and continuous improvement.
  • Establish engineering standards and encourage consistent use of best practices.
  • Balance hands-on engineering with technical leadership, team development, and delivery responsibilities.
  • Depending on the position level, support or lead hiring, onboarding, performance feedback, career development, and workforce planning.
• Data Solution Design and Development
  • Lead the design, development, implementation, and support of scalable batch and streaming data solutions.
  • Develop reusable patterns for data ingestion, transformation, storage, and access.
  • Integrate data from APIs, databases, event streams, third-party platforms, and enterprise systems.
  • Remain actively involved in architecture discussions, solution design, code reviews, troubleshooting, and complex problem-solving.
  • Ensure data solutions are reliable, maintainable, secure, scalable, and cost-effective.
• Engineering Excellence and Production Support
  • Promote modern engineering practices, including version control, automated testing, continuous integration, automated deployment, and infrastructure automation.
  • Establish standards for data quality, validation, monitoring, lineage, and observability.
  • Optimize data pipelines, databases, queries, and storage solutions for performance and cost.
  • Support production operations and provide leadership during critical incidents, root-cause analysis, and preventative improvements.
  • Identify opportunities to reduce technical debt and operational risk.
• Product Collaboration and Delivery
  • Partner with Product Managers, Architects, Engineers, Analysts, and business stakeholders to understand priorities and deliver effective data solutions.
  • Translate business and product needs into technical roadmaps and clearly defined engineering work.
  • Lead or contribute to planning, prioritization, estimation, and delivery activities.
  • Manage risks, dependencies, resource needs, and competing priorities.
  • Communicate progress, technical recommendations, risks, and dependencies to stakeholders and leaders.
• Data Governance, Security, and Standards
  • Promote data governance practices, including metadata management, data lineage, classification, and data quality.
  • Ensure solutions meet applicable security, privacy, governance, and regulatory requirements.
  • Partner with Architecture, Security, Risk, and Governance teams to align solutions with enterprise standards.
  • Support the responsible access, use, storage, and movement of enterprise data.
• Innovation and Continuous Improvement
  • Evaluate emerging technologies, frameworks, and engineering practices that may improve data capabilities.
  • Identify opportunities to increase automation, simplify development, and improve engineering productivity.
  • Support cloud modernization and data platform transformation initiatives.
  • Promote continuous learning and the responsible use of generative and agent-based artificial intelligence tools.

Qualifications

• Managing Engineer: 5 or More Years of Experience
  • 5 or more years of experience designing, developing, and supporting data solutions, data pipelines, or enterprise software systems.
  • 1 or more years of experience providing technical leadership, mentorship, coaching, or project leadership.
  • Experience guiding engineers through technical mentorship and knowledge sharing.
  • Strong hands-on experience developing data pipelines using Python, Java, Scala, or a comparable programming language.
  • Experience designing and supporting batch or streaming data solutions.
  • Experience with Apache Spark, Apache Kafka, Apache Flink, dbt, or comparable technologies.
  • Strong knowledge of SQL, NoSQL databases, data modeling, and data storage concepts.
  • Experience integrating data from APIs, databases, event streams, and third-party systems.
  • Experience with automated testing, continuous integration and delivery, deployment automation, and DevOps practices.
  • Experience with Docker and Kubernetes.
  • Strong communication, collaboration, and stakeholder management skills.
  • Ability to influence technical outcomes and lead through expertise.
• Managing Engineer: 7 or More Years of Experience
  • 7 or more years of experience designing, developing, and supporting data solutions, data pipelines, or enterprise software systems.
  • 3 or more years of experience leading, mentoring, or managing technical professionals.
  • Experience with coaching, performance management, career development, hiring, and team development.
  • Strong hands-on experience developing data pipelines using Python, Java, Scala, or a comparable programming language.
  • Experience designing and supporting scalable batch and streaming data solutions.
  • Experience with Apache Spark, Apache Kafka, Apache Flink, dbt, or comparable technologies.
  • Strong knowledge of SQL, NoSQL databases, data modeling, and data architecture.
  • Experience integrating data from APIs, databases, event streams, and enterprise systems.
  • Experience optimizing data platforms, pipelines, databases, and storage solutions for performance and cost.
  • Experience implementing automated testing, continuous integration and delivery, observability, and engineering excellence practices.
  • Experience with Docker and Kubernetes.
  • Strong communication, decision-making, and stakeholder management skills.
  • Ability to balance hands-on engineering, people leadership, and delivery accountability.
• Desirable Qualifications
  • Experience with data services and platforms in Microsoft Azure or Amazon Web Services.
  • Hands-on experience with Microsoft Fabric, including Lakehouse, Warehouse, Data Pipelines, Dataflows Gen2, Semantic Models, and Fabric Notebooks.
  • Experience with Azure DevOps, GitHub Actions, Jenkins, or similar tools.
  • Experience with Datadog or another monitoring and observability platform.
  • Experience supporting or leading cloud modernization or data platform transformation initiatives.
  • Experience building reusable data frameworks, shared services, internal platforms, or developer tools.
  • Knowledge of data governance, metadata management, data lineage, privacy, security, and regulatory requirements.
  • Experience supporting large-scale enterprise data products.
  • Familiarity with generative and agent-based artificial intelligence tools used to improve engineering productivity.

Supervisory Responsibilities

This job has supervisory duties.

Compensation

Compensation offered for this role is 120,000.00 - 193,725.00 annually and is based on experience and qualifications.