Experience in understanding and translating data, analytic requirements and functional needs into technical requirements while working with global customers.
Design cloud-native data architectures that support scalable, real-time, and batch processing.
Build and maintain data pipelines to support large scale data management in alignment with data strategy and data processing standards.
Define strategies for data modeling, data integration, and metadata management.
Strong experience in database, data warehouse, data lake design & architecture.
Leverage cloud platforms (AWS, Azure, GCP, etc.) for data storage, compute, and analytics services such as Azure Synapse, AWS Redshift, or Google BigQuery.
Experience in Database programming using multiple flavour of SQL.
Implement data governance frameworks, including data quality, lineage, and cataloging.
Collaborate with cross-functional teams, including business analysts, data engineers, and DevOps teams.
Experience in Big Data ecosystem - on-prem (Hortonworks/MapR) or Cloud (Dataproc/EMR/HDInsight/Databricks/SnowPark)
Evaluate emerging cloud technologies and recommend improvements to data architecture.
Experience in any orchestration tool such as Airflow/Oozie for scheduling pipelines
Hands-on experience in using Spark Streaming, Kafka, Databricks, Snowflake, etc.
Experience working in an Agile/Scrum development process.
Experience to optimize data systems for cost efficiency, performance, and scalability.
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Data Architect - Pharma • Chicago, IL, US
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