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| Job Location | London |
| Education | Not Mentioned |
| Salary | Competitive salary |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
| Job Type | Permanent, full-time |
Job Description This international FTSE100 company seeks a Lead Big Data Security Engineer to join its growing information security engineering division. Initially, the role will be based from home and post-Covid, you will work 2 days a week from home and 3 days a week from the office in the South East (Surrey). The firm is seeking an Information Security Engineering Lead with strong technical expertise in Big Data, who is interested in joining this new squad to help build and operate this service and the underlying products. As a key member of this team, you will be working as part of the small empowered, customer-centric squad to deliver this consolidated, easy to use data platform for reporting and analytics of security datasets. As the Engineering Lead, you will ensure adherence to policies, standards and best practices and provide technical expertise to internal and external stakeholders. Using advanced technical capabilities to lead changes to security processes and procedures, you will review complex security issues and lead security solutions from identification to implementation. The successful candidate will have experience in: Building Azure Data Factory ingestion pipelines and ETL jobs to consume data feeds from security source systems (e.g. Nanologs, Azure feeds, O365, AD etc.) Use Azure Databricks or Azure Data Explorer to convert and stage feeds for use in production Designing and implementing Continuous Integration / Continuous Delivery (CI/CD) solution using standards for the squad. Creation and managing of data pipelines, transformation and storage. Build monitoring and alerting mechanisms for data pipelines and transformation. Build flexible data APIs that support the ingestion, or the consumption needs of the data lake and its customers. Lead conversations to derive value out of our data and enable operational excellence. Managing infrastructure for Big Data and data pipelines. Experience in DevOps on Azure and AWS cloud environments. Extensive experience of developing using the Azure and AWS analytics components including Azure / AWS Data Lake, Power BI, Data Factory, HDInsight, SQL DB/DW and SSIS. ETL Tooling in Azure, AWS and Palantir cloud environments Agile and DevOps development methodology and concepts as applied to data driven analytics projects. Including CI/CD Coding, security testing best practice and standards. Designing, building, and operating analytics solutions using Azure, AWS, or Palantir cloud technologies. Data Management experience e.g. data profiling, large volume data handling Automated data driven testing Scripting Languages: Python, C#, Java, PowerShell (at least one of them) DB Programming: relational dbs (SQL) , nonrelational (NoSQL,MongoDB, Cassandra)