Senior Data Engineer

Stelle nicht auf LinkedIn

🕒 vor 21 Tagen

🇺🇸 Vereinigte Staaten – Remote

💵 $139.000 - $181.500 / Jahr

⏰ Vollzeit

🟠 Senior

🚰 Dateningenieur

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ClickUp

WebsiteLinkedInAlle Stellen

1001 - 5000 Mitarbeiter

Gegründet 2017

☁️ SaaS

⚡ Produktivität

🏢 Unternehmen

💰 €400.000.000 Series C - ClickUp im 2021-10

SaaS • Productivity • Enterprise

ClickUp ist eine cloudbasierte SaaS-Arbeitsmanagement- und Produktivitätsplattform, die Projekte, Dokumente, Chat, Zeiterfassung, Automatisierungen und KI-gesteuerte "Super Agents" in einem einzigen Arbeitsbereich zusammenführt. Sie hilft Teams und Unternehmen, Arbeitsabläufe zu optimieren, fragmentierte Software-Ensembles zu ersetzen und die Produktivität mit Integrationen, anpassbaren Agenten/Workflows sowie Sicherheit und Compliance auf Unternehmensniveau zu steigern.

Beschreibung

• Own the technical architecture of ClickUp's data platform, making design decisions that balance scalability, cost, reliability, and velocity. • Define and drive the technical roadmap for data infrastructure in partnership with leadership. • Design systems at scale: build frameworks, abstractions, and patterns that other engineers use daily. • Lead complex, cross-team technical initiatives spanning data engineering, analytics engineering, data science, and data analytics. • Drive cost optimization across cloud infrastructure and compute, turning efficiency into a competitive advantage. • Build and evolve our data pipelines using AWS serverless (Lambda, Fargate, Step Functions, Kinesis, S3, DynamoDB, Aurora), Snowflake, and dbt. • Establish and champion engineering standards: observability, testing, CI/CD, code review, and documentation practices. • Design and maintain infrastructure for AI/ML workloads, including LLM frameworks, feature pipelines, training data systems, and model monitoring. • Mentor senior engineers, provide technical guidance through design reviews, and raise the overall engineering quality of the team. • Influence org-wide technical decisions and represent data engineering in company-level architecture discussions.

🎯 Anforderungen

• Significant professional experience in data engineering or backend/infrastructure engineering, with at least 3 years operating at a senior or staff level. • Proven track record of owning architecture for data platforms or large-scale distributed systems. • Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK). • Expert-level SQL and Snowflake (or equivalent cloud data warehouse) knowledge, including performance tuning and cost optimization. • Strong experience with dbt and modern ELT/ETL patterns at scale. • Advanced Python skills with emphasis on building reusable libraries, frameworks, and tooling. • Hands-on experience with orchestration frameworks (Airflow, Dagster, or Prefect) in production environments. • Experience building data infrastructure for AI/ML: feature stores, training pipelines, embedding pipelines, model serving, or LLM integration. • Deep understanding of streaming and event-driven architectures (Kinesis, Kafka, or equivalent). • Mastery of CI/CD, Git workflows, containerization (Docker), and deployment automation. • Strong communication skills: ability to write technical RFCs, influence without authority, and translate complex trade-offs for non-technical stakeholders. • Track record of mentoring and growing engineers, with a multiplier mindset.

🏖️ Vorteile

• Equity • 401k • Health, Dental, and Vision insurance • Spending accounts • Life & Disability • Paid parental leave • Flexible paid time off • Enhanced employee assistance program • Employee wellness stipend • Professional development stipend