Senior Engineer

Stelle nicht auf LinkedIn

🕒 vor 5 Tagen

🇺🇸 Vereinigte Staaten – Remote

⏰ Vollzeit

🟠 Senior

🧑‍💻 Full-Stack-Entwickler

👻 Geisterscore 14%

infoinfo

🗣️🇺🇸🇬🇧 Englisch erforderlich

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Logo of Nexus Cognitive

Nexus Cognitive

51 - 200 Mitarbeiter

Gegründet 2018

💼 Beratung

📣 Marketing

📦 Logistik

💰 Series unknown im 2024-07

Consulting • Marketing • Logistics

Nexus Cognitive ist eine anpassbare Intelligenzschicht und offene Datenplattform, die über den Unternehmensdatensystemen liegt, um Daten AI-bereit zu machen, ohne die bestehende Infrastruktur zu ersetzen. Sie bietet ein universelles Anfrage-Gateway, automatische Anreicherung, zentrale Governance und einen verwalteten Full-Stack-Service, der schnelle (30-tägige) AI-Implementierungen, niedrigere Gesamtkosten (TCO) und unternehmensgerechte Sicherheit und Compliance ermöglicht. Nexus Cognitive fördert Umsatz, Kundenbindung, betriebliche Intelligenz und Risikointelligenz, indem es Daten über Data Warehouses, Lakehouses und Cloud-Plattformen hinweg vereint, den Geschäftskontext bewahrt und das Toolwachstum minimiert.

Beschreibung

• Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and deliver data from internal and external sources • Develop and optimize data models and schemas supporting analytics, reporting, and downstream application needs • Monitor pipeline health, troubleshoot data quality issues, and implement alerting and observability practices • Partner with analytics, product, and engineering teams to translate data needs into durable data solutions • Improve performance, scalability, and cost-efficiency of existing data infrastructure • Write technical documentation and contribute to standards for testing, code review, and deployment • Participate in on-call or incident response rotations as needed to support production data systems

🎯 Anforderungen

• 4+ years of professional experience in data engineering or a closely related discipline • Strong proficiency in SQL and at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java) • Hands-on experience building and operating ETL/ELT pipelines in a production environment • Experience working with cloud data platforms (e.g., AWS, GCP, or Azure) and modern data warehousing tools • Solid understanding of data modeling, data quality, and pipeline orchestration concepts • Comfort working with large, complex datasets and diagnosing data issues independently • Experience with orchestration tools such as Airflow, Dagster, or similar • Familiarity with streaming data technologies (e.g., Kafka, Kinesis) • Experience with dbt or similar transformation frameworks • Exposure to infrastructure-as-code practices (e.g., Terraform) • Prior experience supporting analytics or data science teams directly

🏖️ Vorteile

• A collaborative team culture built on curiosity and respect • Challenging work where your contributions clearly matter • A leadership team that invests in learning and development • Opportunity to work at the intersection of cloud, data, and AI innovation

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