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You have experience managing multiple high-visibility and high-impact enterprise cybersecurity initiatives with cross-functional teams while maintaining superior results through risk analytics, data governance, and insight generation.
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You have passion and expertise in one or more of the following areas: risk analytics, data analytics, machine learning, SQL, Python, cloud security, network security, vulnerability management, data protection, threat intelligence & investigations, and identity & access management.
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As a candidate for this role, you’re able to seamlessly switch from executive-level risk conversations to diving deep into controls and technology to driving high level, strategic discussions around metrics, data, and risk analytic reporting solutions.
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Specifically, this experience must be in writing Big Data engineering jobs for large scale data integration in AWS. Prior experience in writing Machine Learning data pipeline using Spark programming language is an added advantage.
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Advanced Analytics - Applied Econometrics, Advanced Calculus, Statistical Methods, Data Visualization, Decision Analytics & Optimization, ML, Big Data, Social Network Analytics. Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP.
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Experience with CRM systems (e.g., Salesforce, Eloqua) and their integration with data warehouses. 12+ years experience as a Data Architect, Data Engineer, or similar role with a focus on data warehousing and marketing data analytics.
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Knowledge of some of the main components of Azure Analytics: Azure Data Processing Technologies (DataFactory, Databricks), Azure Big Data Technologies, Databricks, Synapse. Data governance – (Purview, Unity Catalogue.
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DevOps Integration: Implement continuous integration and continuous deployment (CI/CD) pipelines using Jenkins and Terraform to automate deployment, monitoring, and scaling of data infrastructure.
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Work you’ll do: Deloitte provides Integrated Risk Management (IRM) services, IT Asset Management (ITAM) including Configuration Management Database (CMDB) Services, and Governance, Risk & Compliance (GRC) services based on the client’s immediate and long-term needs.
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Collaborate with cross-functional IT teams, including Data Governance, Digital Strategy & Execution, Enterprise Architecture & Data Analytics to understand Finance and CPG/Pharma/Manufacturing Enterprise business requirements to identify opportunities for improvement.
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Data Engineering: Develop ETL processes, data ingestion pipelines, and data transformations to support data integration and analytics requirements. Architecture and Design: Architect robust and scalable data pipelines and analytics solutions on Azure Databricks, leveraging services such as Apache Spark, Delta Lake, and MLflow.
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Implement data governance processes for item master data maintenance. Work as the liaison between Engineering, technology and procurement teams on development and optimization of product data across multiple systems / processes with focus on data quality, integrity and governance.
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Reporting to the Chief Information Officer the Data Engineer is primarily responsible for developing and maintaining robust data integration pipelines between various systems such as internal OLTP databases, third-party vendor platforms, and an Enterprise Data Warehouse (EDW), scoping requirements for advanced reports, developing metrics and dashboards, and making recommendations for process improvement based on analysis of historical data.
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Maintain item data integrity, quality control and governance of items in appropriate systems and tools. Identify opportunities to leverage technology to improve ability to compile, analyze, and report item creation and data (e.g. smartsheet, access, excel, JDE, Cantor, AQ, etc.
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Support migration of data - item master data - from legacy systems to new systems. Cielo has partnered with Cornerstone Building Brands to hire 4 Product- Data Analysts for an 18-month contract and 1 full-time, permanent.
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big data governance integration jobs Title: big data engineer
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