Cloud Platform Lead Consultant or Senior Consultant

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. 

• →Design, deploy, and manage highly available database platforms including Apache Cassandra, PostgreSQL, Redis, Valkey, Amazon Redshift, and Google BigQuery across multi-cloud environments.
• →Build, operate, and optimize data streaming infrastructure using Amazon MSK (Kafka), Google Pub/Sub, and Apache Flink to support real-time and batch data pipelines.
• →Develop and maintain infrastructure-as-code, CI/CD pipelines, and cloud automation using Python and industry-standard tooling to enable repeatable, secure deployments.
• →Implement comprehensive monitoring, alerting, and observability for data platform services to proactively detect and resolve issues before they impact customers.
• →Partner with application development teams to troubleshoot, tune, and optimize application performance, query patterns, and data access layers backed by team-managed platforms.
• →Administer and optimize analytics and query engines including Starburst Galaxy and AWS Athena to deliver performant, cost-effective access to large-scale datasets.
• →Lead incident response, root cause analysis, and post-incident reviews for production database and streaming systems; drive remediation and preventive improvements.
• →Participate in an on-call rotation to provide 24x7 support for mission-critical data infrastructure.
• →Evaluate and adopt emerging technologies—including AI agents and MCP servers—to automate operational tasks, improve developer experience, and accelerate DevOps workflows.
• →Contribute to capacity planning, disaster recovery, security hardening, and cost optimization initiatives across the data platform estate.
• →Ability to review application source code, identify root causes of performance or reliability issues, and contribute targeted fixes or optimization guidance in collaboration with development teams.
• →Demonstrated ability to rapidly adopt unfamiliar technologies and deliver production-ready solutions within days to a week; strong self-directed learning with a track record of picking up new platforms, frameworks, and tools independently.
• →Proven ability to guide and advise software development teams on application-level performance tuning, query optimization, code-level improvements, and production troubleshooting—functioning as a technical authority on data platform usage patterns.
• →Strong understanding of distributed systems principles including high availability, fault tolerance, consistency models, and disaster recovery.
• →Excellent problem-solving, communication, and documentation skills with a track record of ownership in on-call and incident management environments.
• →Ability to read, debug, and analyze Java application code including Spring Boot and microservice frameworks; proficiency in JVM diagnostics including heap dump analysis, GC tuning, thread dump interpretation, and connection pool (e.g., HikariCP) troubleshooting.

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• 3-5 or more years of overall software engineering or infrastructure experience, with at least 2-4 years in site reliability engineering, DevOps, or platform engineering operating production systems at scale.
• Demonstrated expertise designing, deploying, and managing cloud infrastructure on AWS and/or Google Cloud Platform, including networking, identity, and security fundamentals.
• Strong hands-on experience with relational and NoSQL databases; production experience with PostgreSQL and at least one distributed database such as Apache Cassandra.
• Production experience operating data streaming platforms; hands-on experience with Apache Kafka (including Amazon MSK) and a solid understanding of streaming fundamentals (partitions, consumer groups, delivery semantics, backpressure).
• Advanced, production-grade Python and Shell scripting development skills, including writing, reviewing, and debugging application code, building custom automation tooling, and developing operational solutions that go well beyond basic scripting.
• Strong experience with infrastructure-as-code (e.g., Terraform, Terraform Enterprise (TFE), Env0), Jenkins, Ansible, Git CI/CD pipelines and container orchestration (e.g., Kubernetes) in production environments.
• Experience implementing and automating monitoring, logging, and alerting solutions for distributed systems (e.g., Prometheus, Grafana, CloudWatch, Datadog, or equivalent), including building automated runbooks and self-healing remediation workflows.
• Proven track record independently leading root cause analysis for complex production incidents that span infrastructure, databases, streaming pipelines, and application code layers.

• Production experience operating and troubleshooting Apache NiFi, including flow design, processor-level debugging, back-pressure configuration, cluster management, and contributing flow-level fixes and optimizations.
• Hands-on operational experience with self-managed Apache Flink, including checkpoint management, state backend configuration, TaskManager memory tuning, job graph analysis, and application-level debugging of streaming jobs under backpressure.
• Deepened experience with Apache Cassandra, PostgreSQL, DynamoDB, Amazon Redshift, ElastiCache and/or Google BigQuery in production environments.
• Advanced experience with Apache Kafka, Apache Flink, Google Pub/Sub and operating streaming workloads across both AWS and GCP.
• Experience administering or optimizing Starburst Galaxy, Trino, or AWS Athena for large-scale analytics workloads.
• Experience building AI agents or Model Context Protocol (MCP) servers to automate DevOps, observability, or operational workflows.
• Hands-on experience with large language models (LLMs), including fine-tuning, prompt engineering, RAG pipeline development, or training custom models for operational and DevOps use cases.
• Familiarity with data pipeline orchestration tools (e.g., Apache Airflow, dbt) and event-driven architectures.
• Experience troubleshooting and supporting applications deployed on enterprise PaaS platforms (e.g., Cloud Foundry, or equivalent) including understanding platform-level resource constraints, routing, and application lifecycle management.
• Working proficiency in Golang sufficient to read production application code, interpret runtime behavior (goroutines, memory, pprof profiling), and contribute targeted performance fixes in collaboration with development teams.
• AWS or Google Cloud professional-level certifications.
• Experience with performance benchmarking, query plan analysis, and database capacity planning for high-throughput workloads.
• Familiarity with application profiling, distributed tracing, and performance diagnostic tooling (e.g., APM, query analyzers, flame graphs) to isolate and resolve end-to-end latency issues.
• Contributions to open-source database, streaming, or infrastructure projects.

Allstate generally does not sponsor individuals for employment-based visas for this position.

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Allstate provides a comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse. Employees eligible to work from home also receive a monthly connectivity reimbursement to help offset internet costs.

When working from home, you must have a dedicated, private workspace free from distractions, along with appropriate desk and seating. Reliable internet is required, with minimum speeds of 50 MB download and 5 MB upload.