Manager, Data Platform & Products - Data Engineering

Job Description

A Data Engineer is responsible for designing, building, and maintaining robust data pipelines/report and infrastructure that facilitate the collection, storage, and processing of large datasets. They ensure data/insight is accessible, reliable, and optimized for analysis by collaborating with data scientists and analysts. Key tasks include data integration, ETL (Extract, Transform, Load) processes and managing databases and cloud-based systems. Data engineers play a crucial role in enabling data-driven decision-making and ensuring data quality across organizations. What will you do in this role Design, develop, and maintain data pipelines to extract data from various sources and populate a data lake and data warehouse. Work closely with data scientists, analysts, and business teams to understand data requirements and deliver solutions aligned with business goals. Use data orchestration, logging, and monitoring tools to build resilient pipelines. Automate data flows and pipeline monitoring to ensure scalability, performance, and resilience of the DI platform. Monitor, troubleshoot, and resolve issues related to the data integration platform, ensuring uptime and reliability. Maintain thorough documentation for integration processes, configurations, and code to ensure easy onboarding for new team members and future scalability. Develop pipelines to ingest data into cloud data warehouses. Establish, modify and maintain data structures and associated components. What should you have Bachelors degree in Information Technology, Computer Science or any Technology stream. 3+ years of developing data pipelines & data infrastructure, ideally within a drug development or life sciences context. Demonstrated expertise in delivering large-scale information management technology solutions encompassing data integration and self-service analytics enablement. Experienced in software/data engineering code practices (including versioning, release management, CI/CD, deployment of datasets, agile & related software tools). Strong working knowledge of at least one large-scale data processing technology (eg, High-performance computing, distributed computing), databases, and underlying technology (cloud or on-prem environments, containerization, distributed storage & databases) Cloud-native, ideally AWS certified. Proven record of analytical thinking and problem solving. Good interpersonal and communication skills (verbal and written). Proven record of delivering high-quality results. Product and customer-centric approach. Innovative thinking, experimental mindset and passion for learning. Required Skills: Business Intelligence (BI), Database Administration, Data Engineering, Data Management, Data Modeling, Data Visualization, Design Applications, Information Management, Software Development, Software Development Life Cycle (SDLC), System Designs