Easetalent is a leading recruiting and consulting firm committed to connecting exceptional talent with their ideal career opportunities. Our mission is to facilitate the growth and success of both our candidates and partner companies by bridging the gap between talent and opportunity. We are currently seeking a dedicated Lead Data Architect to join our client in USA.
Job Summary: The Lead Data Architect will spearhead the design, development, and implementation of scalable and robust data architecture solutions. This role involves leading Databricks migration projects, architecting data pipelines and lakes using the PySpark framework and Delta Live Tables (DLT), and ensuring seamless transitions of existing data workflows. The ideal candidate will have extensive experience in data architecture, particularly within the healthcare domain, and possess strong leadership skills to mentor junior team members.
Key Responsibilities:
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Lead the design, development, and implementation of scalable and robust data architecture solutions.
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Drive Databricks migration projects, ensuring seamless transition and optimization of existing data workflows.
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Architect and implement data pipelines and lakes using the PySpark framework and Delta Live Tables (DLT).
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Migrate existing workloads from SSIS, Azure Data Factory, Python, SQL Server, and other data processing and transformation tools without altering existing functionality.
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Design and optimize data models for efficient storage, retrieval, and analysis of large volumes of structured and unstructured data.
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Develop and maintain Python scripts for data processing, transformation, and automation tasks.
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Collaborate with cross-functional teams to gather and analyze data requirements, translating them into technical specifications.
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Ensure data quality and integrity across the organization by implementing data governance policies and best practices.
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Design and implement large-scale data lake solutions, leveraging cloud platforms such as AWS and Azure.
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Provide technical leadership and mentorship to junior team members, fostering a culture of continuous learning and innovation.
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Stay updated with emerging technologies and trends in data architecture, cloud computing, and healthcare domain advancements.
Requirements:
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Bachelor's degree in Computer Science, Engineering, or a related field.
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12+ years of experience in data architecture, with a focus on designing and implementing data solutions.
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Proven experience leading Databricks migration projects and expertise in PySpark, Airflow, SSIS, Azure Data Factory, SQL Server, and Python scripting.
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Strong background in designing and implementing large-scale data lake solutions.
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Experience working in the healthcare domain, with a deep understanding of healthcare data standards and regulations (e.g., HIPAA, PHI).
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Exposure to cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
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Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and stakeholders.
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Strong problem-solving and analytical skills, with a focus on delivering innovative and scalable data solutions.
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Relevant certifications in data architecture, cloud computing, or related areas are a plus.