Data Platform Engineer

About Lantern

Lantern is the specialty care platform connecting people with the best care when they need it most. By curating a Network of Excellence comprised of the nation's top specialists for surgery, cancer care, infusions and more, Lantern delivers excellent care with significant cost savings to employers and their workforces. Lantern also pairs members with a dedicated care team, including Care Advocates and nurses, for the entirety of their care journey, helping them get back to good health, back to their families and back to work. With convenient access to specialists nationwide, Lantern means quality care is within driving distance for most. Lantern is trusted by the nation's largest employers to deliver care to more than 6 million members across the country. Learn more about us at lanterncare.com.

Lantern's data organization is moving from a centralized model - where the platform team owns most pipeline delivery - toward one where domain teams (Data Engineering, Data Ops, Analytics Engineering) build and own their own data products, and the platform team's job is to make that possible. This role is core to that shift: building and administering the self-serve infrastructure, governance automation, and access controls that domain teams build on top of, rather than building domain pipelines directly.

Location: Hybrid - at least 3 days/week in our Dallas, TX offices

Responsibilities:

Platform Administration

Administer the Azure Databricks and Unity Catalog platform against the architecture standards set by the data architecture committee - workspace and metastore configuration, catalog and schema structure, cluster policies, and compute cost management, including spend-by-team visibility and chargeback reporting. Feed back to the standards owners where a standard is blocking teams or no longer fits how the platform is being used.

Self-Serve Enablement

Build the self-serve infrastructure layer - provisioning workflows, templates, and access patterns that let domain teams stand up and manage their own data products without depending on the platform team for every change.

Postgres Database Administration (Lakebase)

Act as the DBA for the platform's Postgres estate - provisioning and decommissioning of Lakebase instances, user and role management, connection configuration, query and index performance tuning, version upgrades, backup and point-in-time recovery, and database incident response. Maintain the sync patterns between Lakebase and the lakehouse.

Infrastructure-as-Code

Build and maintain Infrastructure-as-Code for the platform using Terraform against Azure - resource groups, networking and private endpoints, Entra ID app registrations, service principals, and Key Vault - so platform changes are reviewable, repeatable, and auditable.

Access & Governance Model

Implement and enforce the platform's approved access model across the lakehouse and the Postgres layer - Unity Catalog grants, OBO (on-behalf-of) authentication patterns, ABAC, row-level security, data masking, and role-based access across engineering, ops, and analytics personas.

Audit & Lineage

Build the audit and lineage layer that makes decentralized ownership auditable - audit logging, lineage capture, sensitivity classification tagging, and the custom event-sourced audit layer needed where Databricks cannot natively capture app-layer events, including incident response when this layer breaks.

Observability

Operate platform observability across Databricks, Lakebase, and supporting Azure services (Datadog integration, metrics and log export, alerting, SLOs) so domain teams get reliability guarantees without building their own monitoring.

Reliability & Disaster Recovery

Execute the infrastructure lifecycle - provisioning, decommissioning, backup and restore validation, and disaster recovery testing for platform and database workloads.

Support Coverage

There is no overnight on-call rotation for this role. Occasional availability outside core hours is expected to support scheduled deployments and major incidents.

CI/CD

Support CI/CD for data workloads across domain teams - deployment pipelines for notebooks, jobs, DLT pipelines, dbt projects, Databricks Asset Bundles (DABs), and Lakebase schema migrations.

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