Cloud & Data Senior Architect
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Job description
Targa is seeking a highly experienced Senior Architect, Data & Cloud Platforms to provide hands-on architecture leadership for the cloud and data-platform environment that supports the company’s evolving enterprise data ecosystem. This role will guide the immediate maturation of Microsoft Fabric and Azure-based data capabilities while defining reliable, scalable, secure, and supportable cloud, database, integration, operational-data, and platform architecture patterns., * Define and maintain reference architectures, standards, patterns, decision records, and roadmaps for enterprise data and cloud platforms across Microsoft Fabric, Azure, and related technologies.
- Define and govern cloud landing-zone and environment architecture for the data ecosystem, including subscription structure, network topology, private connectivity, identity integration, environment segmentation, policy enforcement, monitoring, and secure platform scalability.
- Provide architecture leadership for Targa’s medallion architecture, including data acquisition, Bronze/Silver/Gold design, semantic and serving layers, data products, and platform interoperability.
- Define operational architecture for Microsoft Fabric and Azure-based data services, including workspace and capacity structure, tenant and environment controls, networking implications, monitoring patterns, workload placement, and production support requirements.
- Design source-aware ingestion patterns for batch, ETL/ELT, change data capture, replication, APIs, event streaming, and near-real-time processing.
- Assess source-system architecture, workload profile, transaction volume, concurrency, query plans, indexing, locking, log usage, network throughput, recovery objectives, and growth before approving ingestion designs.
- Define and apply patterns such as read replicas, availability-group secondaries, log-based CDC, incremental extraction, workload isolation, throttling, scheduling, and resource governance to protect operational source systems from analytical impact.
- Establish architecture standards for platform capacity, workload isolation, performance testing, throughput modeling, concurrency management, and scale-out patterns across Fabric, Azure data services, databases, and integration workloads.
- Define reliability architecture patterns for data and cloud platforms, including resiliency, failover, disaster recovery, backup and recovery, service continuity, capacity thresholds, observability, and production-readiness standards.
- Define architecture patterns for development, test, staging, and production environments, including deployment pathways, release controls, configuration management, rollback patterns, and production-change readiness.
- Incorporate cost, consumption, and scalability considerations into architecture decisions, including workload placement, capacity sizing, storage tiering, compute patterns, and vendor/platform tradeoffs.
- Partner with database, infrastructure, application, and source-system owners to resolve performance, availability, replication, security, and recovery implications of data movement and analytics access.
- Shape data architectures for commercial and trading capabilities, including ETRM integration, market and reference data, near-real-time positions, P&L, exposure, risk, settlement, valuation, audit lineage, and high-concurrency analytical workloads.
- Define architecture for operational and industrial data, including historians, PI, SCADA, time-series telemetry, event data, Maximo, and the integration of OT and enterprise data.
- Architect secure cloud connectivity and platform controls, including private endpoints, virtual networks, identity, SSO, SCIM, RBAC/ABAC, secrets, encryption, audit logging, and zero-trust patterns.
- Guide the implementation of data catalogs, metadata, lineage, master data, data quality, classification, privacy, fine-grained access, and governance technologies where they are required to support reliable platform operations and governed data consumption.
- Evaluate cloud services, databases, replication technologies, integration platforms, and vendor products using architecture, performance, security, resilience, operability, interoperability, and total-cost criteria.
- Lead architecture reviews and technical design sessions; document exceptions, dependencies, risks, and decisions in a practical and timely manner.
- Create proofs of concept and production pilots for emerging platform, cloud, database, integration, and reliability capabilities while defining measurable success criteria and production-readiness requirements.
- Mentor data engineers, platform engineers, database professionals, and solution architects; improve technical depth through reusable patterns, playbooks, and coaching.
- Partner with platform leadership to establish capacity models, observability, RTO/RPO, disaster recovery, release practices, and sustainable production operations.
- Other duties as assigned.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Management Information Systems, or a related technical field; equivalent relevant experience will be considered.
- 15+ years of progressive enterprise technology experience, including 10+ years in data, database, cloud, integration, or platform architecture roles.
- 7+ years of hands-on experience designing, administering, tuning, or architecting large enterprise relational database platforms such as SQL Server, Azure SQL, Oracle, PostgreSQL, or comparable technologies.
- Demonstrated experience designing ingestion and replication patterns that protect source-system performance, availability, recoverability, and transaction processing.
- Deep experience with Microsoft Azure architecture, including storage, compute, networking, private connectivity, identity, security, monitoring, integration, and data services.
- Experience architecting modern cloud data platforms and lakehouse/warehouse environments using Microsoft Fabric, Snowflake, Databricks, Azure Synapse, or comparable technologies.
- Experience designing reliable and scalable cloud landing zones, network topologies, environment segmentation, policy controls, and production-ready platform architectures.
- Experience with ETL/ELT, log-based CDC, data replication, APIs, event streaming, orchestration, and near-real-time data movement.
- Strong knowledge of database performance engineering, query optimization, indexing, concurrency, HA/DR, backup and recovery, RTO/RPO, data tiering, and security.
- Experience defining capacity, resiliency, observability, workload isolation, release, and environment-promotion patterns for enterprise data and cloud platforms.
- Experience architecting secure multi-cloud or hybrid-cloud environments using private endpoints, network segmentation, identity and access management, encryption, logging, and audit controls.
- Experience defining enterprise data architecture standards across data management, security, governance, metadata, lineage, quality, and master data.
- Experience leading architecture reviews and influencing delivery teams, infrastructure, security, application owners, vendors, and executive stakeholders without relying solely on direct authority.
- Strong written and verbal communication, documentation, facilitation, and technical problem-solving skills.
- Regular and reliable attendance., * Experience in midstream, oil and gas, chemicals, manufacturing, utilities, banking, or another transaction-intensive or asset-intensive environment.
- Experience architecting data platforms for commodity trading, ETRM, supply and trading, risk, market data, position management, P&L, settlement, or commercial optimization.
- Experience with Maximo, Oracle, SQL Server, RightAngle or comparable ETRM platforms, and large enterprise source systems.
- Hands-on experience with Microsoft Fabric, ADLS Gen2, Azure Data Factory, Azure Data Explorer, Event Hubs, Logic Apps, Functions, Azure DevOps, Entra ID, and Power BI.
- Experience with Snowflake, Databricks, CDC tools such as Qlik or Fivetran, Kafka, data catalogs, and cloud RBAC technologies.
- Experience designing high-concurrency or sub-minute data platforms for risk, operational, trading, or industrial use cases.
- Experience with Kubernetes, containers, infrastructure as code, CI/CD, and platform automation.
- Experience designing and operating reliable cloud environments with capacity planning, monitoring, backup/recovery, disaster recovery, workload isolation, and production support requirements.
- Experience with OT/IT data integration, PI historians, SCADA, time-series platforms, or industrial data management.
- Microsoft Azure, database, cloud architecture, data engineering, or related technical certifications.
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