Data Operations Specialist

Emploi pas sur LinkedIn

🕒 il y a 9 jours

🇺🇸 États-Unis – Télétravail

⏳ Contrat

🟡 Intermédiaire

🟠 Senior

⚙️ Opérations

🦅 Parrain de Visa H1B

Cette entreprise a parrainé des visas H1B par le passé.

👻 Score fantôme 14%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Scicom Infrastructure Services

Site WebLinkedInTous les Emplois

11 - 50 employés

🏢 Entreprise

☁️ SaaS

🤝 B2B

Enterprise • SaaS • B2B

Scicom Infrastructure Services est une organisation de conseil et de services technologiques de premier plan dans le secteur. L'entreprise se concentre sur la fourniture de solutions technologiques de haute qualité, fiables et rentables pour soutenir les objectifs commerciaux des organisations de premier plan du secteur privé et public. Scicom propose une gamme de services incluant la gestion de la performance d'entreprise, les services gérés, l'architecture d'entreprise, la gestion de projet, la gestion des infrastructures et la gestion des applications. Elle collabore avec des entreprises comme AppDynamics, BigPanda, DataDog et AWS pour la performance des entreprises et des applications, la corrélation d'événements et l'automatisation, la surveillance d'entreprise, la surveillance cloud et les solutions ITSM. Scicom offre un support opérationnel global, 24/7, et est reconnue pour sa capacité à gérer efficacement l'infrastructure mondiale. L'entreprise a été nommée comme l'une des entreprises privées à la croissance la plus rapide en Amérique par Inc 5000 à plusieurs reprises.

Description

• Monitor the health, availability, performance, and capacity of Databricks workspaces, jobs, pipelines, clusters, SQL warehouses, and related cloud services • Provide day-to-day operational support for production Databricks environments • Monitor and troubleshoot ETL, ELT, streaming, API, and file-based data pipelines • Restart, rerun, recover, reprocess, backfill, reconcile, and remediate failed workflows and data loads • Review driver and executor logs, Spark UI metrics, cluster event logs, audit logs, and application telemetry to identify root causes • Support Databricks Workflows, Lakeflow, Delta Live Tables, Auto Loader, Structured Streaming, and batch-processing workloads • Maintain cluster, serverless compute, instance pool, cluster policy, SQL warehouse, and environment configurations • Coordinate platform upgrades, runtime and library updates, deployments, releases, changes, rollbacks, and post-deployment monitoring • Serve as first- or second-level support for production incidents; triage, coordinate response, provide status updates, escalate, and conduct root-cause analyses • Maintain incident, problem, service-request, change, deployment, and operational records • Develop and maintain dashboards, alerts, operational reports, health indicators, SLIs, and SLOs • Monitor job success, latency, processing duration, utilization, freshness, quality, and compute consumption • Validate data contracts, schemas, record counts, control totals, data quality, lineage, audit evidence, and governance requirements • Support identity, access, entitlement, Unity Catalog, secrets, security, privacy, backup, recovery, retention, archival, and disaster-recovery activities • Analyze resource consumption, job duration, query performance, storage, and workload patterns; recommend cost and performance optimizations • Create and maintain operational procedures, troubleshooting guides, escalation matrices, runbooks, inventories, configuration documentation, and recovery requirements • Identify automation and continuous-improvement opportunities and participate in operational-readiness reviews

🎯 Exigences

• Bachelor’s degree in computer science, information technology, data engineering, information systems, or a related field, or equivalent professional experience • At least four years of experience in data operations, production support, data engineering, cloud operations, DevOps, platform support, or a related technical role • At least two years of hands-on experience supporting Databricks environments or production Databricks workloads • Experience supporting production ETL, ELT, batch, or streaming data pipelines • Working knowledge of Databricks, Apache Spark, PySpark or Python, SQL, Delta Lake, Databricks Workflows or Jobs, cloud object storage, data pipeline monitoring, log analysis, and troubleshooting • Experience investigating failed jobs, delayed pipelines, schema issues, data discrepancies, and performance problems • Familiarity with medallion architecture and Bronze, Silver, and Gold data layers • Experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud • Experience using ticketing and service-management tools such as ServiceNow, Jira, or a comparable platform • Experience with monitoring, alerting, logging, or observability tools • Understanding of incident, problem, change, and release-management processes • Ability to write and maintain technical procedures and operational documentation • Strong analytical, organizational, communication, and troubleshooting skills • Ability to work effectively with engineers, business analysts, architects, security teams, and nontechnical stakeholders • Ability to support multiple production priorities in a structured and timely manner • Preferred: Databricks Certified Data Engineer Associate or Professional; Databricks Certified Associate Developer for Apache Spark; Microsoft Azure, AWS, or Google Cloud certification • Preferred: Experience with Unity Catalog, Delta Live Tables, Lakeflow, Auto Loader, Structured Streaming, Databricks SQL, cloud services, CI/CD tools, observability platforms, APIs, Kafka, Event Hubs, Kinesis, Airflow, dbt, Snowflake, Power BI, data contracts, schema registries, metadata management, data lineage, data-quality frameworks, OCDS, procurement, contracting, financial or public-sector data, regulated or high-security environments, SLAs and 24-hour support, disaster recovery, backup, archival, and operational-resilience testing

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV