Data Engineers will lead working on building scalable data and analytics solutions. This role is key to end-to-end solution delivery, stakeholder management, collaboration with other engineering teams, participation in architecture design discussions, and will guide and mentor others. The ideal candidate will have outstanding communication skills, proven data design, and implementation capabilities, business acumen, and a highly developed drive to deliver results.

Major Responsibilities:

• Provide leadership in building data models/architecture, query optimization and automation, ELT, and data governance frameworks with scalability, efficiency, and reliability
• Adhere to agile project management frameworks and set the direction of data science initiatives
• Develop strong partnerships with Data Analytics, MDM, Data Science, Product, Engineering, and other data teams and understand their data needs
• Apply a wide range of Data Engineering/Technological skills for developing, maintaining, and modernizing our data platform suites/eco-system in real-time processing
• Implement large-scale data ecosystems including data management, governance, the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
• Improve our Data Engineering stack through containerization, data modeling, data quality, data pipeline automation, and data integration
• Responsible for driving coding, design, and showcasing best practices while leading by example.
• Keep informed of the latest technology trends and innovations, especially in the areas of customer data platforms, master data management, marketing resource management, digital asset management, web content management, mobile, and social media
• Full lifecycle implementation experience using various SDLC methodologies
• Strong interpersonal skills and the ability to communicate complex technology solutions to senior leadership, gain alignment, and drive progress

• BS/MS degree in Computer Science or other technical field or equivalent, preferred but not required
• 10+ or more years of hands-on experience in designing, building and maintaining data pipelines
• Azure data store models expertise a must
• 7+ or more years of experience with scalable cloud-based data warehouses such as Azure Data Warehouse and Snowflake
• Experience with data catalog, ingestion, streaming, pipeline, orchestration tools such as informatica, and Alation.
• Experience Salesforce Cloud eco-system Service, Marketing, Commerce preferred.
• Industry experience in master data, metadata, data architecture, data governance, data quality and data modeling
• Coding proficiency in at least one or more modern programming language Python, PySpark, Java, Node.JS, React JS, Restful API
• Familiarity with Kubernetes, Docker, Kafka and with different modeling techniques such as data vault.
• Experience in data quality tools, including data profiling, cleansing and identity resolution
• Experience leading workstreams or small teams • Strong oral and written communication skills, including presentation skills
• Plus to have Experience with Life Sciences Pharmaceutical Commercial and Sales Operations group, including insights