Job Seekers, Please send resumes to resumes@hireitpeople.com

Minimum Position Qualifications:

• Extensive knowledge of data principles, patterns, processes, and practices
• Any experience defining evolutionary data solutions and underlying technologies.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Experience with SQL database design, data modeling
• Analyze and organize raw data.
• Build data systems and pipelines.
• Evaluate business needs and objectives.
• Interpret trends and patterns.
• Conduct complex data analysis and report on results.
• Demonstrated written and oral communication skills.
• Basic understanding of network and data security architecture
• Strong knowledge of industry trends
• Knowledge in a minimum of two of the following technical disciplines: data warehousing, data management, analytics development, data science, application programming interfaces (APIs), data integration, cloud, servers and storage, and database management
• Experience building cost effective and performance driven solutions using elastic architectures in Microsoft Azure leveraging Cosmos, Azure Data Factory, Azure Synapse and Databricks Platforms.
• Experience with SQL and NoSQL applications on Big Data Platforms
• Experience with SSAS Tabular models, Power BI, Dataflows and DAX
• Experience with Azure Data Platform stack: Azure Data Lake, Azure Synapse, Data Factory and Databricks
• Experience with Python, Spark and SQL
• Any experience with streaming technologies like Kafka, IBM MQ and EventHub
• Experience with Google cloud Platform is a plus

Key Responsibilities / Essential Job Functions

• Drive digital innovation by leveraging 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.
• Present opportunities with cost/benefit analysis to leadership to shape sound architectural decisions.
• Lead the analysis of the technology environment to detect critical deficiencies and recommend solutions for improvement..
• Interpreting data, analyzing results using statistical techniques.
• Developing and implementing data analyses, data collection systems and other strategies that optimize statistical efficiency and quality.
• Acquiring data from primary or secondary data sources and maintaining databases
• Promote the reuse of data assets, including the management of the data catalog for reference.