Top Tech Jobs & Startup Jobs

Lead enterprise cloud platform strategy, architecture, engineering, and operations. Build secure, scalable, cost-effective cloud, Kubernetes, automation, developer platform, and AI capabilities. Establish governance, security, observability, reliability, disaster recovery, FinOps, and SRE practices. Lead cloud, platform, DevOps, and SRE teams while partnering with application, security, data, and product stakeholders and communicating investment priorities to senior leadership.

Leads enterprise data and integration architecture, including platform-to-MDM and platform-to-application integrations. Owns solution architecture from requirements through operational support, establishes data governance and architectural standards, designs scalable data warehouses, and guides cross-functional teams. The role also provides technical leadership, conducts architecture reviews, ensures security and performance alignment, resolves complex integration challenges, and influences enterprise-wide technology decisions.

Lead enterprise technology and business transformation programs for critical infrastructure operations. Manage roadmaps, scope, budgets, resources, risks, dependencies, governance, reporting, and value realization. Partner with business, engineering, operations, finance, and technology leaders to deliver measurable outcomes. Lead and develop program management teams, drive stakeholder alignment, improve operational efficiency, and ensure solutions meet business, security, compliance, and operational requirements.

Designs, develops, and maintains Power BI business intelligence solutions. Responsibilities include data modeling, ETL, dashboard and report creation, data analysis, performance optimization, documentation, stakeholder collaboration, and end-user training. The role requires ensuring data accuracy, reliability, scalability, and actionable insights for data-driven decision-making.

Lead operational support for SnapLogic and dbt data integration pipelines, including monitoring, incident response, root-cause analysis, SLA management, performance optimization, and release coordination. Manage a small support team, on-call rotations, ticket triage, runbooks, and operational metrics. Partner with client stakeholders and data platform teams to prioritize issues, communicate status, and deliver permanent fixes.

Own production support for SnapLogic and dbt data integration pipelines, including monitoring, incident response, ticket triage, SLA adherence, troubleshooting, and root-cause remediation. Lead support engineers, manage on-call and escalations, maintain documentation, coordinate releases and change management, assess performance, and report operational metrics. Partner directly with clients and data platform teams to prioritize issues, communicate status, and optimize pipelines and transformations.

Build and operate cloud-native Azure data pipelines from source ingestion through Bronze-Silver-Gold transformation layers. Develop Fabric Dataflow Gen2 pipelines, Delta Tables, Synapse SQL evaluation logic, and event-driven integrations using Azure Event Hub and Event Grid. Perform data quality validation, schema reconciliation, lineage verification, and parallel-run testing across multiple domains. Extend configuration-driven frameworks and support sprint-based delivery across concurrent workstreams.

Leads the design, development, and deployment of scalable cloud-native data pipelines for enterprise analytics and reporting. Establishes data engineering standards, governance, security, privacy, and compliance practices. Makes architectural decisions, mentors engineers, conducts reviews, translates business needs into technical solutions, and owns end-to-end data initiatives in an Agile environment.

Designs, develops, and maintains Snowflake-based data solutions, including optimized SQL queries, stored procedures, ETL/ELT pipelines, and data transformations. Performs validation, troubleshooting, performance tuning, and implements data governance, security, and scalability best practices. Collaborates with engineers, analysts, architects, and stakeholders to deliver cloud data warehouse solutions.

Build and scale reusable data modernization assets, including discovery tools, code-generation frameworks, converters, validation patterns, playbooks, runbooks, and estimation aids. Consolidate delivery learnings, drive accelerator adoption across teams, measure reuse, and train delivery pods on accelerators and AI-assisted engineering. Lead modernization programs involving dbt, Snowflake, migration planning, reconciliation, parallel runs, and cutover execution.