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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in architecting and implementing large-scale data platforms, with a strong focus on distributed processing, cloud systems, and production software. Proven ability to lead cross-team initiatives, establish engineering standards, and drive technical delivery while ensuring reliability, performance, and security.
Highest-signal resume keywords
Distributed ProcessingData ModelingSQL ProficiencyCloud InfrastructureArchitectural Judgment
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Backend ProgrammingData Processing FrameworksETL ImplementationStreaming SystemsChange-Data CaptureAnalytical DatabasesProduction Software DevelopmentDebugging Critical Code PathsSchema EvolutionIncremental Processing
Soft Skills
Technical LeadershipMentorshipCross-Team CollaborationProblem SolvingCommunication
Tools & Technologies
CI/CDContainer OrchestrationWorkload SchedulersMonitoring ToolsIncident Response Systems
Industry Keywords
Data PlatformsLakehouse ArchitecturesCloud ServicesProduction SafeguardsObservability
Tech Stack
Tools & technologiesCloudDistributed SystemsETLSQL
About the role
Key responsibilities & impact- Define and guide the technical vision for a key DGX Cloud Data Platform domain
- Own architecture, interfaces, and growth while addressing scale, reliability, performance, security, compatibility, and cost
- Lead technical delivery of complex cross-team initiatives
- Translate unclear requirements into architectures and interfaces, coordinate implementation, write essential code, resolve technical obstacles, and guide secure production integrations
- Architect, implement, and evolve batch and streaming systems for fleet, capacity, utilization, cost, scheduling, and operational telemetry
- Build shared platform capabilities, libraries, workflow/orchestration abstractions, deployment tooling, and implementation standards
- Lead high-impact production investigations across pipelines, applications, query engines, distributed processing, storage, networks, and cloud services
- Establish root causes, drive durable resolution, and implement preventive improvements
- Drive engineering standards for testing, data quality, reconciliation, lineage, SLOs, observability, secure identities, least privilege, release readiness, and auditable deployments
- Establish data models, semantics, ownership boundaries, and serving interfaces
- Provide tables, APIs, automation, dashboards, and internal applications for trusted DGX Cloud data access
- Provide technical leadership through architecture and build reviews, mentorship of senior engineers, and evidence-based tradeoff resolution
Requirements
What you’ll need- 8+ years of relevant industry experience
- Bachelor’s degree or equivalent experience
- Master’s degree or equivalent experience in Computer Science, Engineering, or a related field
- Sustained record of personally crafting, implementing, and operating production software, data platforms, databases, or distributed systems
- End-to-end technical ownership of a multi-system platform domain or complex cross-team engineering initiative
- Deep hands-on experience with distributed processing, analytical or relational databases, production ETL, change-data capture, streaming or event processing, or backend and cloud systems handling large data volumes
- Strong software engineering fundamentals and production proficiency in a backend or systems language
- Deep experience with data-processing and platform libraries or frameworks
- Experience crafting reusable abstractions, reviewing substantial changes, and debugging critical code paths
- Strong SQL and data-modeling skills
- Practical depth in query execution, incremental processing, schema evolution, consistency, analytical consumption, idempotency, replay, late-arriving data, partial failure, and cross-system correctness
- Skill diagnosing failures using logs, metrics, traces, query plans, profiles, and controlled experiments
- Strong architectural judgment across reliability, performance, cost, security, compatibility, and maintainability
- Experience guiding major migrations or architectural changes across teams without interrupting production service
- Experience establishing production safeguards and engineering practices adopted by multiple teams, including automated testing, CI/CD, monitoring, alerting, rollback, incident response, and secure deployment
- Deep experience with distributed data processing and lakehouse architectures, or equivalent large-scale database/data-processing platforms
- Experience operating distributed streaming or event-driven systems, including partitioning, consumer behavior, flow control, replay, delivery guarantees, and schema evolution
- Experience scaling, migrating, or improving performance of relational, distributed, time-series, object-storage, or searchable-content data systems
- Background operating cloud infrastructure, container orchestration, workload schedulers, compute or GPU clusters, and fleet-scale telemetry
- Experience defining and owning production adoption of agentic systems or workflow automation, focusing on evaluation, permissions, observability, failure recovery, and measurable improvements
Benefits
Comp & perks- Highly competitive salaries
- Comprehensive benefits package
- Equity
- Benefits for you and your family