We are seeking a Data Solutions Architect with deep expertise in the R&D domain of the Biotech/Pharma industry. In this vital role, you will be responsible for designing, implementing, and optimizing scalable and high-performance data solutions that support enterprise analytics, AI-driven insights, and digital transformation initiatives. The ideal candidate will have a strong background in modern cloud-based data architectures and a proven ability to lead a team in a Scaled Agile environment, ensuring a future-ready data ecosystem.
Roles & Responsibilities
- Architecture & Strategy: Design and implement scalable, modular, and future-proof data architectures that support R&D initiatives. You will develop enterprise-wide data frameworks that ensure data is governed, secure, and accessible across various business domains.
- Data Pipelines & Optimization: Lead the development of high-performance data pipelines for both batch and real-time data processing. You will optimize query performance and storage strategies to enhance scalability, cost-efficiency, and analytical capabilities.
- Governance & Compliance: Drive data governance strategies, ensuring that security, compliance, access controls, and lineage tracking are embedded into all enterprise data solutions.
- Agile Leadership & Collaboration: Lead Scaled Agile (SAFe) practices, including Program Increment (PI) Planning and other ceremonies. You will collaborate with business stakeholders, product teams, and technology leaders to align data architecture strategies with organizational goals.
- Innovation & Best Practices: Act as a trusted advisor on emerging data technologies and trends. You will implement DataOps best practices, including CI/CD for data pipelines and automated monitoring.
Qualifications
- A Doctorate degree with 3-5+ years of experience, a Master's degree with 6-8+ years of experience, or a Bachelor's degree with 8-10+ years of experience in Computer Science, IT, or a related field.
- Experience in data architecture, enterprise data management, and cloud-based analytics solutions.
- Expertise in Databricks, cloud-native data platforms, and distributed computing frameworks like Apache Spark and Apache Airflow.
- Strong proficiency in modern data modeling techniques, including dimensional modeling, NoSQL, and data virtualization.
- Hands-on experience with CI/CD for data solutions, DataOps automation, and infrastructure as code (IaC).
- Experience with SQL/NoSQL databases and vector databases for large language models.
- Certifications such as AWS Certified Data Engineer and Databricks Certificate are preferred.
Soft Skills
- Leadership & Strategy: Strong problem-solving, strategic thinking, and technical leadership skills.
- Collaboration: Proven ability to collaborate with cross-functional and global teams to drive successful data initiatives.
- Communication: Strong verbal and written communication skills, with the ability to effectively present complex technical concepts.
- Adaptability: The ability to learn quickly, manage multiple priorities, and work effectively in a fast-paced environment.
