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Job Title: DE Architect Industry/Field: Healthcare and Life Sciences Experience: 7-12 years Tredence differentiates itself from other analytics services firms by enabling last mile adoption of insights. We drive true business impact by uniting our strengths in business analytics, data science, and software engineering. We help our clients deliver on the artificial intelligence imperative, in a practical and demystified way. As a Data Engineering Architect specializing in Databricks, you will lead the design and implementation of scalable data solutions in the Healthcare and Life Sciences domain. Success in this role means delivering robust architecture that accelerates data-driven decision-making while ensuring data quality and governance. You will collaborate closely with cross-functional teams to translate complex business requirements into effective data engineering strategies. This position plays a critical role in advancing Tredence's mission to drive measurable business impact through innovative data insights. Design, architect, and implement end-to-end data lakehouse solutions using Databricks, Delta Lake, and data catalog technologies. Lead data modelling and data quality initiatives to ensure reliable, consistent, and well-governed datasets for analytics and AI applications.Develop and optimize PySpark, Python, and SQL pipelines to support complex data processing workflows.Collaborate with business stakeholders and technical teams to understand requirements, translate them into scalable data engineering solutions, and support last mile adoption of insights.Define standards and best practices for data architecture, governance, and security aligned to Healthcare and Life Sciences regulations.Mentor and guide engineering teams on architecture principles, tooling, and performance optimization in Databricks environments.Demonstrate 7-12 years of relevant experience in data engineering architecture, ideally within Healthcare and Life Sciences or related industries. Possess deep expertise in Databricks architecture, including Delta Lake, Lakehouse, and data catalog implementations.Exhibit strong proficiency in data modelling, data quality frameworks, and governance best practices.Be skilled in developing and optimizing data pipelines using PySpark, Python, and SQL.Hold a BE/B.Tech degree in Computer Science, Engineering, or a related discipline.Experience with cloud platforms such as AWS, Azure, or GCP that integrate with Databricks.Familiarity with Healthcare and Life Sciences data compliance standards (e.g., Knowledge of DevOps, CI/CD pipelines, and automation for data engineering workflows.Certification(s) in Databricks or related data engineering technologies.Exposure to AI/ML model deployment pipelines and MLOps practices.Engage in impactful projects at the intersection of advanced data engineering and healthcare, driving meaningful business and societal outcomes. - Enjoy a flexible work mode (work_mode) that promotes work-life balance and personal growth. Job Title: DE Architect Industry/Field: Healthcare and Life Sciences Experience: 7-12 years Tredence differentiates itself from other analytics services firms by enabling last mile adoption of insights. We drive true business impact by uniting our strengths in business analytics, data science, and software engineering. We help our clients deliver on the artificial intelligence imperative, in a practical and demystified way. As a Data Engineering Architect specializing in Databricks, you will lead the design and implementation of scalable data solutions in the Healthcare and Life Sciences domain. Success in this role means delivering robust architecture that accelerates data-driven decision-making while ensuring data quality and governance. You will collaborate closely with cross-functional teams to translate complex business requirements into effective data engineering strategies. This position plays a critical role in advancing Tredence's mission to drive measurable business impact through innovative data insights. Design, architect, and implement end-to-end data lakehouse solutions using Databricks, Delta Lake, and data catalog technologies. Lead data modelling and data quality initiatives to ensure reliable, consistent, and well-governed datasets for analytics and AI applications.Develop and optimize PySpark, Python, and SQL pipelines to support complex data processing workflows.Collaborate with business stakeholders and technical teams to understand requirements, translate them into scalable data engineering solutions, and support last mile adoption of insights.Define standards and best practices for data architecture, governance, and security aligned to Healthcare and Life Sciences regulations.Mentor and guide engineering teams on architecture principles, tooling, and performance optimization in Databricks environments.Demonstrate 7-12 years of relevant experience in data engineering architecture, ideally within Healthc
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