Data Platform Engineering Manager

Berkshire Hathaway Homestate Companies•Bay Area, California, CA

3d•$174,250 - $222,020•Hybrid

About The Position

Berkshire Hathaway Homestate Companies’ Workers Compensation Division is hiring a Data Platform Engineering Manager to lead the team responsible for its enterprise data platform. The role is accountable for the platform’s performance, reliability, security, scalability, and cost efficiency, and oversees the selection, implementation, operation, and continuous improvement of technologies used to store, process, and move organizational data. The Manager leads and develops database engineers, oversees operational data stores and analytical platforms, directs data transformation and movement, and advances automation through Infrastructure as Code and GitOps practices aligned with the Autonomous Composable Development model. The position remains hands-on across relational, NoSQL, and analytical data platforms, serves as the final technical escalation point for complex incidents, and participates in a mandatory scheduled 24x7 on-call rotation. The role also establishes platform standards and practices for security, compliance, change management, monitoring, high availability, disaster recovery, performance, and cost management. It works across DevOps, Application Engineering, Security, and Analytics, and communicates platform risks, technology trade-offs, and investment proposals to Director and VP-level leaders.

Requirements

Bachelor’s degree in Computer Science, Management Information Systems, Data Engineering, or a related discipline.
At least 10 years of experience in database administration, data engineering, or data platform operations.
At least 5 years in a team lead, supervisory, or management role with direct people-management responsibility.
Hands-on experience with more than one database platform.
Experience with database redundancy and high availability, such as Always On, geo-replication, or equivalent.
Cloud data platform experience, such as Azure SQL, Fabric, or Databricks, and ETL/ELT experience.
Experience with IaC and automation tools such as Terraform, Azure DevOps, and PowerShell, including automating database provisioning and schema deployment.
Expert-level knowledge of SQL Server 2016–2022, Azure SQL, and Managed Instance.
Working knowledge of Microsoft Fabric and familiarity with relational and NoSQL platforms beyond the Microsoft stack, such as Postgres, MySQL, Cosmos, or Mongo, sufficient to assess and recommend appropriate stores for workloads.
Knowledge of ETL/ELT patterns and tools including Azure Data Factory, SSIS, Fabric pipelines, HVR, and Databricks, and of medallion and lakehouse patterns.
Experience with Terraform, Azure DevOps, Git-based workflows, PowerShell, and Python; repository and GitOps fluency sufficient to review and direct the team’s IaC contributions.
Knowledge of Dynatrace monitoring, NYDFS Part 500, SOC audit compliance, and PII handling.
Ability to present technology decisions and trade-offs to Director, VP, and Analytics leadership; write clear standards, runbooks, change records, performance feedback, and investment proposals; proactively communicate status, risks, and team capacity; and explain technical data concepts in terms of business outcomes.

Nice To Haves

Master’s degree.
Two or more certifications strongly preferred: Microsoft Fabric Analytics Engineer (DP-600), Azure Data Engineer Associate (DP-203), Azure Database Administrator Associate (DP-300), or equivalent certifications in non-Microsoft data platforms.
Working experience with at least one of Postgres, MySQL, Cosmos, or Mongo, alongside SQL Server, Azure SQL, and Managed Instance.
Claude or LLM usage for data engineering.
Track record designing and operating data systems in regulated industries.

Responsibilities

Directly supervise database engineers, including setting day-to-day direction, prioritizing workloads, managing performance, conducting 1:1s and reviews, and developing team capabilities.
Develop team depth across relational, NoSQL, and analytical platforms, and improve proficiency in automation, IaC, and GitOps.
Address gaps between defined standards and demonstrated team practices; schedule on-call rotations and escalation coverage.
Resolve cross-team blockers with peer leaders and surface risks, gaps, and disagreements in writing when identified.
Own the operational data store estate, including OLTP and NoSQL platforms such as MS SQL and Cosmos, and recommend appropriate stores for workloads.
Own data transformation and movement, including ADF, Airflow, and replacement of current HVR and SSIS approaches.
Operate the analytical data platform, including OneLake and Bronze, Silver, and Gold tiers, to established platform standards.
Select technologies and manage their reliability, performance, cost, licensing, and capacity in accordance with organizational guidelines.
Define GitOps schema management, IaC provisioning, and lifecycle automation standards; author and review T-SQL, PowerShell, and IaC templates for database provisioning and schema deployment.
Move work from manual execution to self-service, including database change management using Liquibase or equivalent tools and automated environment refreshes.
Coordinate the team’s contributions to cross-team automation initiatives, delivering post-configuration requirements, provisioning inputs, and integration constraints to partner engineering teams.
Promote Claude and LLM tools for schema documentation, data lineage, query optimization, and automation, and mentor engineers in their use.
Remain hands-on in the design, implementation, and administration of Azure SQL, Managed Instance, SQL Server, and other adopted relational, NoSQL, and analytical platforms; act as the final technical escalation point for complex incidents.
Own redundancy planning, high-availability design, and failover execution, including Always On availability groups, geo-replication, and tested failover procedures; validate HA/DR through regular testing and remediate single points of failure.
Define Dynatrace monitoring standards and oversee platform performance, availability, and capacity monitoring; lead complex performance tuning and bottleneck resolution.
Participate in the scheduled 24x7 on-call rotation, review post-incident reports, and drive remediation to completion.
Implement and enforce data classification, PII handling, retention, and audit compliance requirements; partner with Security on data security aligned with NYDFS Part 500 and SOC requirements.
Ensure team adherence to documentation and change management standards, and review and approve change records before implementation.
Lead tooling evaluations and vendor assessments; coordinate capacity planning, budgeting, and staffing with the Director.
Represent the data platform in cross-functional work with DevOps, Application Engineering, Security, and Analytics, and resolve technical boundaries between teams.
Communicate technology trade-offs and platform risks to Director and VP-level leaders, and author proposals for investments involving significant budget or operational risk.