Senior Platform Engineer
- Sibitalent Corp.
9 Hours Ago
NA
W2
Remote
8-10 Years
Required Skills: AWS, Azure, data engineering, cloud engineering, platform engineering, DevOps, database engineering
Job Description
Summary:
- Design, implement, maintain, and support the company’s enterprise data platform and the supporting infrastructure, integrations, and services required to deliver reliable, secure, scalable, and cost-effective data capabilities.
- Partner with data engineering, infrastructure, security, application development, architecture, and business technology teams to support data ingestion, transformation, storage, analytics, integration, governance, and operational data requirements across cloud, on-premises, SaaS, and third-party environments.
- Serve as a technical resource for data platform implementation, connectivity, automation, security, performance, reliability, and modernization initiatives.
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 GCP.
- 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.
