IT Enterprise Architect - Data and Analytics

Key Skills

Aartificial intelligence, Apache Hadoop, AWS, Azure, Data Architecture, Data Lake, Data science techniques, Data Visualization, Database, ETL/ELT technologies, Google Cloud Platform (GCP), IT, Machine learning techniques, NoSQL, PowerBI, Python Programming, PyTorch, QlikView, SPARK Programming, TensorFlow

Job Description

Get to Experience a collaborative environment where teamwork is celebrated with flexibility that enhances balance and an inclusive atmosphere that is welcoming to all! 

Have the Opportunity to chart your own course, challenge yourself, and acquire new capabilities to build a rewarding and fulfilling career. We reward employees with competitive pay and incentives to recognize skills, competencies, and contributions to business results.  

The IT Enterprise Architect - Data and Analytics is a core member of the IT EA Center of Excellence and will take a strategic view of business activity systems supported and enabled by IT. The Data and Analytics EA works to integrate business planning with IT planning, address portfolio-level analysis, with a view to cross-organizational standardization, integration and optimization, and produces road maps for major changes and innovations. Identifies and coaches other architects to broaden experience/expertise and develops and maintains succession plans. Actively engage in or leads technology deliverables for transformation / corporate programs.

Your Key Responsibilities:

• Constrain waste and issues caused by point solution proliferation and duplication
• Drive solution and technical data collection maintain a summary description of the enterprise and its systems
• Manage standards, principles, processes reference models and patterns
• Contribute to business strategy and processes with advice on where changes and innovations can help
• Develop roadmaps for changes and at a strategic, executive-level
• Develops external relationships to advance technical architectures
• Analyze the latest trends in technology architecture like new frameworks or best practices and educating tech departments about them.
• Coordinating the work across domains and guide and govern architects working at lower levels.
• Ensure solutions created meet business requirements while delivering tech forward advances

Your Qualification Profile:

• Bachelor’s Degree required in Information Technology, Computer Science, Data Engineering, Data Science or a related field
• Agile methodologies with focus in the data and analytics domain
• Impactful communication and influence involving multi-disciplinary teams and senior leadership
• Experience in a Global IT role is preferred
• People management experience is preferred
• 5+ plus years of IT experience
• Good understanding, Data lakes, data structures, data models, power platform, reporting solutions, analytic platforms.
• Data modeling tools

• Data modeling and database design: proficient in creating data models and designing databases to store and manage large volumes of data.
• Data integration and ETL: deep understanding of integrating data from various sources and performing Extract, Transform, and Load (ETL) processes to ensure data quality and consistency.
• Data governance and compliance: knowledge of data governance and compliance regulations, such as GDPR, CCPA, HIPAA, and SOX, and how to implement them in the organization's data management practices.
• Big data and cloud computing: expertise in utilizing big data technologies such as Data Lakes, Hadoop, Spark, and NoSQL databases in cloud computing platforms
• Relational databases: should have a strong understanding of relational databases, including SQL and database management systems such as Oracle, MySQL, and Microsoft SQL Server.
• Big data technologies: such as Azure Datalake, Apache Hadoop, Apache Spark, and NoSQL databases such as MongoDB, Cassandra, and Couchbase.
• Data integration tools: familiar in using data integration tools such as Informatica, SAP PI/PO, SAP CPI, and API frameworks.
• Cloud computing platforms: prior experience working with cloud computing platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform.
• Data visualization tools: The architect should be proficient with data visualization tools such as Power BI, and QlikView.
• Machine learning and AI technologies: familiarity with machine learning and AI technologies such as Python, TensorFlow, and PyTorch.