Sr. Enterprise Data Architect
Location: Bloomington, IL or Alpharetta, GA
You will be in charge of developing data architecture plans, data analytics initiatives, cloud transformation and data governance. All about data lakes and putting data into the cloud. Datawarehouse data catalog BI ATL Meta data Azure storage Azure datalake storage azure data bricks azure AD Azure ML Hadoop Spark Sqoop Hive Flume Storm Kafka
This role will be responsible for developing data architecture plans and driving the plans to fruition in collaboration with business and IT. You will play a key role in driving a number of data and analytics initiatives including: cloud data transformation, data governance, data quality, MDM, and data science. You will define cloud reference architectures to promote reusable patterns and promote best practices for data integration and consumption.
- Create, maintain, and govern architectural views and blueprints depicting the Business and IT landscape in its current, transitional, and future state.
- Recommend long-term direction on strategic advancements within the technical portfolio.
- Define and maintain standards for artifacts containing architectural content within the operating model.
- Build a Community of Practice for solutions architecture while leveraging architectural tools, processes, and practices.
- Offer insight, guidance, and direction on the usage of emerging trends and technical capabilities.
- Strong cloud data architecture knowledge with experience developing architecture strategies and plans to enable cloud data transformation, MDM, data governance, and data science capabilities.
- Design reusable data architecture and best practices to support batch/streaming ingestion, efficient batch, real-time, and near real-time integration/ETL, integrating quality rules, and structuring data for analytic consumption by end uses.
- Ability to lead software evaluations including RFP development, capabilities assessment, formal scoring models, and delivery of executive presentations supporting a final recommendation.
- Well versed in the Data domains (Data Warehousing, Data Governance, MDM, Data Quality, Data Catalog, Analytics, BI, Operational Data Store, Metadata, Unstructured Data, ETL, ESB).
- Experience with cloud data technologies such as Azure data factory, Azure storage, Azure data lake storage, Azure data bricks, Azure AD, Azure ML etc.
- Experience with big data technologies such as Hadoop, Spark, Sqoop, Hive, Flume, Storm, and KafkaBachelor’s degree and at least 15 years of equivalent work experience that provides knowledge of and exposure to fundamental theories, principal and concepts
- 2 years of lead experience.