Junior Identity Security Metrics Consultant & Databricks Analyst

Description We are seeking a Senior Data Engineer to support our client with data ingestion, data deduplication, and data tagging for migration of a large-scale data environment into Databricks. The ideal candidate will also bring hands‑on expertise in end‑to‑end data pipeline management, including data ingestion from diverse sources, de‑duplication of large‑scale datasets, and data tagging to support downstream analytics, governance, and machine learning workflows. Roles and Responsibilities (including but not limited to) Design, develop and maintain scalable data ingestion pipelines to onboard structured, semi‑structured and unstructured data from batch and streaming sources (e.g., APIs, databases, flat files, message queues) into the Azure/Databricks environment. Implement de‑duplication strategies across large‑scale datasets using deterministic and probabilistic matching techniques to ensure data integrity and reduce redundancy within the Data Lake. Develop and enforce data‑tagging frameworks to classify, label and annotate datasets with appropriate metadata (e.g., sensitivity, source, domain, lineage) to support data governance, discoverability and compliance requirements. Assist with operationalising deployments and support of cloud services for ETL operations. This will include standardising and automating processes and workflows, creating documentation/knowledge articles, and overall assisting operations staff who have limited experience in cloud. Written and oral presentations to high‑level CIO management on status of current efforts. Possess skills and experience in business management, systems engineering, operations research and management engineering; typically with a specialisation in a particular technology or business application and keeping abreast of technological developments and industry trends. Assist with deployment, configuration and management of Azure Cloud environment. Assist with migration of existing ETL jobs into Azure/Databricks cloud environment. Ability to share optimisation and efficiencies with the larger team and management. Ability to automate solutions to repetitive problems/tasks. Basic Qualifications Eligible for a Position of Public Trust, including U.S. citizenship or permanent residency, five years of U.S. residency and no more than six months of international travel in the past five years (excluding travel for U.S.‑based work). Bachelor’s degree and 13 years of experience; a degree from an accredited College/University in the applicable field is preferred. Four additional years of relevant experience in lieu of a college degree is required, or if the degree is not in the applicable field then four additional years of related experience is required. 5+ years of experience designing and implementing data ingestion pipelines using tools such as Spark Structured Streaming or equivalent technologies. 5+ years of experience applying de‑duplication techniques at scale, including record linkage, fuzzy matching and entity resolution across structured and unstructured datasets. 5+ years of hands‑on experience with metadata management and automated classification tools to support data governance and lineage tracking. 5+ years of experience working with unstructured data. 2+ years of experience using Databricks or other Spark‑based platforms. Fluency in at least one scripting language: Python, Perl, Ruby or equivalent. Desired Skills Integration of Git in continuous deployment and experience with DevOps monitoring tools. Experience with one or more of the following products and technologies: SAS, Python, C++, Hadoop, SQL database/coding, Oracle, Amazon S3, natural language processing (NLP). Visualization tools such as Tableau and QLIK. Strong skills and experience in Cloud Operations support in Azure. #J-18808-Ljbffr Idexcel