Radiant Systems Inc · 21 hours ago
AWS Data Architect
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Responsibilities
Lead technical teams to promote business intelligence, analytics, and AI solutions across the company.
Advise and coach teams including technical product owners, data scientists, architects, and engineers.
Design and implement enterprise operating models for global and federated data and analytics capabilities.
Contribute to data and analytics business strategies and own the technology enablement strategy.
Develop the architecture to support next-generation data products, self-service analytics, and data democratization.
Define the future state technology architecture for data and analytics.
Ensure operational efficiency with governed data democratization.
Qualification
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Required
Bachelor’s or Master's degree in Computer Science, Information Science, Management Information Systems, or a related field.
10+ years working with structured, semi-structured, and unstructured data.
10+ years of IT experience in the pharmaceutical industry.
8+ years of experience designing and implementing data solutions on AWS (e.g., Databricks, Informatica, S3, Athena, etc.).
4+ years using data management tools such as Databricks, Informatica, and ETL tools.
Strong knowledge of AI data preparation and tools.
Experience with big data engineering, cloud, and open-source technologies.
Proficient in software engineering, SQL, Python, Scala, R, and Java, with experience in Spark, Airflow, and streaming services.
Expertise in data architecture, warehousing, and data wrangling.
Familiar with traditional big data systems like Hadoop and Redshift, and BI tools like Tableau and PowerBI.
Proven ability to lead cross-functional teams and drive technology strategies.
Strong leadership skills in building consensus and achieving goals through collaboration.
Excellent interpersonal and communication skills.
Ability to prioritize and manage projects in a dynamic environment.
Strong problem-solving skills with attention to detail and urgency.
Experience enabling product development using big data analytics in pharma.
Strong technical knowledge of life science production systems and risk evaluation in future designs.