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The Data Architect Intermediate will join the Data Management IM Customer Team and focus on development Data and Analytics solutions, working closely with business partners and stakeholders to meet their decision-support requirements.
This role will work with the Customer Experience Division to support data analysis and equip the business to make data-driven decisions. We use Scala and SQL to perform Data Preparation and Tableau to create self-service dashboards. The team uses the latest in Big Data technologies such as StreamSets, Hadoop and Spark.
Accountabilities will include:
Develop big data solutions by designing data architectures, including business architecture definition, data storage, data analytics, data transformation, and data access
Provide delivery leadership in the design, deployment and data conversion of complex enterprise data solutions
Responsible for creation, comprehensive understanding, maintenance and communication of logical and physical data models and mapping documents
Work closely with data engineers to design high performing and scalable data solutions
Support advanced business analytics and statistically-based data analysis projects to drive business value
Responsible for creation and communication of data architecture standards and best practices, and data movement and mapping design
Establish and participate in data management processes including data lineage, data profiling, data quality management, data stewardship and governance
Advise team members, business partners and customers from a strategic perspective.
Position Requirements
To make an immediate contribution, the Data Architect Intermediate will bring the following skills:
Several years' experience in software development preferably in data & analytics solutions
Understanding of traditional and modern data ingestion, data storage, data processing and data access processes
Strong SQL and Analytic skills with experience in large and complex datasets
Working knowledge in delivering business intelligence or large-scale data warehouses/data lakes using technologies such as Hadoop, Spark, ETL Tools of Oracle, IBM, Teradata and/or similar technology
Experience with data profiling, data analysis and data quality framework.
Experience with Agile/Scrum development methodologies
Excellent verbal and written communication skills
Ability to constructively resolve conflict, manage expectations for competing priorities, and drive towards business goals.
Preferred additional skills:
Experience in Data Engineering (Spark SQL, Scala, Python), Unix Shell Script and Scheduling tools like Control-M
Experience with reporting solutions like Tableau, Microsoft Power BI or similar visualization tools.
Experience with Data Governance framework
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