Senior Databricks Engineer

🕒 il y a 25 jours

🗣️🇺🇸🇬🇧 Anglais requis

Airflow

Amazon Redshift

Azure

BigQuery

Cloud

Kafka

Spark

Terraform

Unity

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HIKE2

51 - 200 employés

🤖 Intelligence artificielle

📋 Conformité

☁️ SaaS

Artificial Intelligence • Compliance • SaaS

HIKE2 est une entreprise de conseil en technologie spécialisée dans l'aide aux clients de secteurs réglementés pour tirer parti des technologies émergentes afin d'accélérer les opportunités et les gains d'efficacité. La société offre des services de conseil expert à l'intersection de la technologie, de la conformité réglementaire et de la croissance stratégique. HIKE2 donne les moyens aux industries telles que les cabinets d'avocats, les services financiers, les compagnies d'assurance, les fournisseurs de services aux entreprises et les entreprises SaaS de haute technologie en proposant des solutions technologiques sur mesure qui répondent à des défis complexes et améliorent l'engagement, l'efficacité et les résultats de croissance. Leurs services incluent l'Intelligence Artificielle, les Données & Analyses, les Solutions Cloud et Salesforce, avec une approche axée sur une stratégie de conformité holistique, une innovation éthique et des initiatives de croissance stratégique.

Description

• Design and build large-scale data platforms on Databricks (Delta Lake, Spark, Unity Catalog) in Azure • Develop and maintain batch and streaming data pipelines for high-volume, complex data sources • Implement medallion/lakehouse architectures from the ground up in greenfield environments • Build and optimize data models to support analytics, reporting, and downstream applications • Integrate Databricks with enterprise systems (APIs, event streams, warehouses, ML workflows) • Tune Spark jobs and pipelines for performance, reliability, and cost at scale • Support production deployments, including CI/CD pipelines, testing, and release management • Partner directly with enterprise clients to translate requirements into working technical solutions • Collaborate with architects, engineers, and data scientists across multiple workstreams • Balance speed and quality, knowing when to move fast and when to harden solutions • Make pragmatic decisions in ambiguous, evolving environments (especially greenfield builds) • Contribute hands-on while also guiding design and approach across the team • Communicate tradeoffs clearly to both technical and non-technical stakeholders • Work within modern engineering practices (version control, code reviews, automated testing) • Demonstrated ability to mentor and guide data engineers and analysts

🎯 Exigences

• Deep Databricks-native expertise, including experience architecting and implementing end-to-end lakehouse solutions that run primarily or entirely on Databricks. • Advanced experience with modern Databricks architecture patterns, including declarative pipelines / Delta Live Tables, Unity Catalog, Delta Lake, workflow orchestration, governance, performance tuning, and operational monitoring. • Familiarity with infrastructure-as-code (Terraform, Bicep), environment provisioning, and CI/CD automation (Github, Azure DevOps) for Databricks-based platforms. • Strong learning agility, technical curiosity, and comfort using AI-enabled development workflows or automation tools to accelerate delivery and improve quality. • Familiarity with other modern cloud data architectures and tools, including cloud-native data warehouses (Snowflake, BigQuery, Redshift), data lakes, orchestration frameworks (Airflow/Astronomer), transformation tools (dbt), catalog/governance platforms, and scalable batch or streaming data processing services (Kafka, Kinesis).

🏖️ Avantages

• medical • dental • vision • 401k • holiday pay • vacation • personal and family sick leave • and more.

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