Role: Databricks Engineer
Location: London (3 days in a week)
Employment: Fulltime
Role Overview
We are seeking an experienced Azure Databricks Data Engineer to design, develop, deploy, and optimize scalable data solutions on Microsoft Azure. The ideal candidate will bring strong hands-on expertise in Azure Databricks, Apache Spark, PySpark, Python, and SQL, with proven experience building production-grade data pipelines, implementing governance through Unity Catalog, and automating deployments using GitLab-based CI/CD and Databricks Asset Bundles.
Key Responsibilities
Design, build, test, and maintain scalable batch and streaming data pipelines using Azure Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake.
Develop reusable ETL and ELT frameworks for data ingestion, transformation, validation, and publishing across lakehouse layers.
Design and manage Delta Tables, including schema evolution, data quality controls, reliability, and performance optimization.
Implement data governance, access control, cataloging, and lineage standards using Unity Catalog.
Create, schedule, monitor, and troubleshoot production workloads using Databricks Jobs and workflows.
Package and deploy Databricks resources across environments using Databricks Asset Bundles and GitLab-based CI/CD pipelines.
Integrate Databricks with Azure Data Lake Storage and Azure Data Factory for secure, reliable data processing.
Optimize Spark workloads, clusters, jobs, and storage patterns for performance, scalability, reliability, and cost efficiency.
Apply coding standards, version control, testing, documentation, and operational best practices using GitLab and Azure DevOps.
Collaborate with architects, analysts, and engineering teams to translate business requirements into maintainable technical solutions.
Required Skills and Experience
Strong hands-on experience with Azure Databricks and the Apache Spark execution architecture.
Advanced proficiency in PySpark, Python, and SQL for large-scale data processing and transformation.
Practical experience with Delta Lake, Delta Tables, Unity Catalog, Databricks Jobs, and Databricks Asset Bundles.
Proven experience designing and operating production-grade ETL or ELT pipelines on Azure.
Hands-on experience implementing CI/CD pipelines using GitLab, including automated validation and multi-environment deployments.
Working knowledge of Azure Data Lake Storage, Azure Data Factory, and Azure DevOps.
Demonstrated ability to tune Spark workloads and troubleshoot data pipeline performance and production issues.
Strong understanding of data engineering, governance, security, version control, testing, and deployment best practices.
Preferred Qualifications
Databricks Certified Data Engineer Associate or Professional certification.
Microsoft Azure data engineering certification or equivalent cloud certification.
Experience with medallion architecture, data quality frameworks, streaming pipelines, infrastructure as code, or lakehouse monitoring.
Exposure to enterprise data governance, regulated environments, or large-scale cloud data modernization programs.
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
