Accountable for developing and delivering technological responses to targeted business outcomes.
Analyze, design, and develop enterprise data and information architecture deliverables, focusing on data as an asset for the enterprise.
Understand and follow reusable standards, design patterns, guidelines, and configurations to deliver valuable data and information across the enterprise, including direct collaboration with 84.51, where needed.
Utilize enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses.
Ensure there is clarity between ongoing projects, escalating when necessary, including direct collaboration with 84.51.
Leverage innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms.
Define high-level migration plans to address the gaps between the current and future state.
Contribute to the development of cost/benefit analysis for leadership to shape sound architectural decisions.
Analyze technology environments to detect critical deficiencies and recommend solutions for improvement.
Promote the reuse of data assets, including the management of the data catalog for reference.
Draft architectural diagrams, interface specifications and other design documents
Must be able to perform the essential job functions of this position with or without reasonable accommodation.
This engineer will be responsible for partnering with users of the platform guide them to follow best practices, building new use cases to support the product teams, support & monitor the platform to keep cost low and improve performance. Partner with external vendors Databricks & azure to learn industry best practices and influence teams in MX to leverage the same.
Demonstrate the company s core values of respect, honesty, integrity, diversity, inclusion, and safety.
Qualifications:
Bachelor's Degree in computer science, software engineering, or related field
4+ years experience in the data development and principles including end-to-end design patterns.
4+ years proven track record of delivering large scale, high quality operational or analytical data systems.
4+ years successful and applicable experience building complex data solutions that have been successfully delivered to customers.
Any experience in a minimum of two of the following technical disciplines: data warehousing, big data management, analytics development, data science, application programming interfaces (APIs), data integration, cloud, servers and storage, and database management
Excellent oral/written communication skills
Desired:
Any experience with SSAS Tabular models, Power BI, Dataflows and DAX
Any experience with Azure Data Platform stack: Azure Data Lake, Data Factory and Databricks
Any experience with Python, Spark and SQL
Any experience with Terraform.
Any experience with streaming technologies like Kafka, IBM MQ and EventHub
Any experience with data science solutions or platforms
Any experience with a variety of SQL, NoSQL, and Big Data Platforms
Any experience building solutions using elastic architectures (preferably Microsoft Azure and Google Cloud Platform)