Senior Platform Engineer (Databricks) || Remote || W2 Role

Responsibilities:

• Design, implement, configure, and maintain enterprise data platforms and supporting cloud infrastructure.
• Support data warehouse, data lake, lakehouse, operational data, integration, and analytical workloads.
• Implement secure connectivity between the enterprise data platform and on-premises systems, cloud environments, vendor platforms, SaaS applications, relational databases, APIs, and file-transfer services.
• Build and maintain platform integrations across databases, object storage, APIs, SFTP, enterprise applications, and third-party data sources.
• Work with infrastructure and networking teams to implement secure cloud and hybrid connectivity patterns.
• Configure and support platform identity, access controls, service accounts, roles, groups, secrets, authentication, encryption, and least-privilege security standards.
• Develop and maintain automated infrastructure and platform deployment processes using infrastructure-as-code and CI/CD technologies.
• Support Git-based source control, release management, environment promotion, and deployment standards for data-platform components.
• Partner with data engineers to implement scalable ingestion and transformation patterns for batch, near-real-time, streaming, API, database, and file-based workloads.
• Support orchestration and scheduling of data pipelines, platform jobs, integrations, and dependent services.
• Configure and manage platform compute, storage, workload isolation, scaling, scheduling, concurrency, resource governance, and cost controls.
• Monitor platform availability, infrastructure health, job execution, query performance, compute utilization, storage consumption, connectivity, and integration health.
• Implement logging, monitoring, alerting, auditing, operational dashboards, and support procedures.
• Troubleshoot data-platform, infrastructure, network, security, performance, and integration issues.
• Support platform upgrades, configuration changes, infrastructure changes, release deployments, and production support.
• Assist with migration of existing warehouse, ETL, database, API, and file-processing workloads into modern data-platform architectures.
• Evaluate workload requirements and help determine appropriate placement across data warehouse, lakehouse, relational database, cloud service, integration, and application platforms.
• Develop reusable engineering patterns, deployment templates, technical standards, and operational documentation.
• Support proof-of-concept environments, platform evaluations, workload testing, performance testing, and migration assessments.
• Collaborate with security, risk, infrastructure, architecture, application, and data teams to incorporate security, availability, resiliency, and compliance requirements into platform implementations.
• Work with internal teams and external vendors to resolve platform, connectivity, integration, and performance issues.
• Maintain technical documentation covering platform architecture, environments, integrations, network connectivity, security controls, operational procedures, deployment processes, and dependencies.
• Identify opportunities for platform simplification, automation, modernization, standardization, reuse, and cost optimization.
• Share technical knowledge and provide guidance to engineers and project teams supporting the enterprise data platform.

Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field; applicable years of experience may be substituted for a bachelor’s degree.
• Minimum of five or more years of progressive experience in data engineering, cloud engineering, platform engineering, DevOps, database engineering, or related technology roles.
• Experience supporting enterprise-scale data platforms, data warehouses, data lakes, or cloud data environments.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Strong understanding of cloud infrastructure, networking, identity and access management, encryption, secrets management, and secure data-platform design.
• Experience working with relational databases, object storage, APIs, file-based integrations, and enterprise data sources.
• Experience with ETL/ELT, pipeline orchestration, data ingestion, transformation, and workload scheduling.
• Experience with source control, CI/CD, and automated deployment processes.
• Experience with infrastructure-as-code technologies such as Terraform, CloudFormation, or equivalent tools.
• Strong SQL skills and working knowledge of data warehouse and analytical database concepts.
• Understanding of modern data architecture concepts including data lakes, warehouses, lakehouses, medallion architectures, batch processing, streaming, CDC, metadata, and governance.
• Experience troubleshooting complex technical issues across cloud infrastructure, databases, networking, and data integrations.
• Ability to communicate technical concepts clearly and professionally to technical and non-technical stakeholders.
• Ability to work effectively across data, infrastructure, security, application, architecture, vendor, and business teams.