Managing Engineer, Data Engineering

Overview

Lead the design, development, and delivery of scalable data solutions supporting digital products, analytics, and business decision-making, combining hands-on engineering with technical leadership, team development, and delivery responsibility.

What you'll do

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

What you'll need

• Managing Engineer (5+ years): 5 or more years of experience designing, developing, and supporting data solutions, data pipelines, or enterprise software systems.
• Managing Engineer (5+ years): 1 or more years of experience providing technical leadership, mentorship, coaching, or project leadership.
• Managing Engineer (5+ years): Experience guiding engineers through technical mentorship and knowledge sharing.
• Managing Engineer (5+ years): Strong hands-on experience developing data pipelines using Python, Java, Scala, or a comparable programming language.
• Managing Engineer (5+ years): Experience designing and supporting batch or streaming data solutions.
• Managing Engineer (5+ years): Experience with Apache Spark, Apache Kafka, Apache Flink, dbt, or comparable technologies.
• Managing Engineer (5+ years): Strong knowledge of SQL, NoSQL databases, data modeling, and data storage concepts.
• Managing Engineer (5+ years): Experience integrating data from APIs, databases, event streams, and third-party systems.
• Managing Engineer (5+ years): Experience with automated testing, continuous integration and delivery, deployment automation, and DevOps practices.
• Managing Engineer (5+ years): Experience with Docker and Kubernetes.
• Managing Engineer (5+ years): Strong communication, collaboration, and stakeholder management skills.
• Managing Engineer (5+ years): Ability to influence technical outcomes and lead through expertise.
• Managing Engineer (7+ years): 7 or more years of experience designing, developing, and supporting data solutions, data pipelines, or enterprise software systems.
• Managing Engineer (7+ years): 3 or more years of experience leading, mentoring, or managing technical professionals.
• Managing Engineer (7+ years): Experience with coaching, performance management, career development, hiring, and team development.
• Managing Engineer (7+ years): Strong hands-on experience developing data pipelines using Python, Java, Scala, or a comparable programming language.
• Managing Engineer (7+ years): Experience designing and supporting scalable batch and streaming data solutions.
• Managing Engineer (7+ years): Experience with Apache Spark, Apache Kafka, Apache Flink, dbt, or comparable technologies.
• Managing Engineer (7+ years): Strong knowledge of SQL, NoSQL databases, data modeling, and data architecture.
• Managing Engineer (7+ years): Experience integrating data from APIs, databases, event streams, and enterprise systems.
• Managing Engineer (7+ years): Experience optimizing data platforms, pipelines, databases, and storage solutions for performance and cost.
• Managing Engineer (7+ years): Experience implementing automated testing, continuous integration and delivery, observability, and engineering excellence practices.
• Managing Engineer (7+ years): Experience with Docker and Kubernetes.
• Managing Engineer (7+ years): Strong communication, decision-making, and stakeholder management skills.
• Managing Engineer (7+ years): Ability to balance hands-on engineering, people leadership, and delivery accountability.

Nice to have

• 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.

Details

• Location: US - Remote.
• This job has supervisory duties.
• Compensation: 120,000.00 - 193,725.00 annually, based on experience and qualifications.
• Candidates offered this position will be required to submit to a background investigation.
• Allstate generally does not sponsor individuals for employment-based visas for this position.