Senior Data Architect

We are looking for a Senior Data Architect to lead enterprise-level data modernization and innovation.

In this highly strategic role, you will design scalable, secure, and future-ready data architectures, modernize legacy systems, and provide trusted technical leadership across both technology and business teams.

This is a unique opportunity to make a company-wide impact by influencing data strategy and enabling smarter, faster decision-making through data.

Key Responsibilities :

Architect & Design : Lead the development of robust, scalable data models, data management systems, and integration frameworks to ensure enterprise-wide data accuracy, consistency, and security.

Domain Expertise : Act as a subject matter expert across key business functions such as Supply Chain, Product Engineering, Sales & Marketing, Manufacturing, Finance, and Legal.

Modernization Leadership : Drive the transformation of legacy systems and manage end-to-end cloud migrations with minimal business disruption.

Collaboration : Partner with data engineers, scientists, analysts, and IT leaders to build high-performance, scalable data pipelines and transformation solutions.

Governance & Compliance : Establish and maintain data governance frameworks including metadata repositories, data dictionaries, and data lineage documentation.

Strategic Advisory : Provide guidance on data architecture best practices, technology selection, and roadmap alignment to senior leadership and cross-functional teams.

Mentorship : Serve as a mentor and thought leader to junior data professionals, fostering a culture of innovation, knowledge sharing, and technical excellence.

Innovation & Trends : Stay abreast of emerging technologies in cloud, data platforms, and AI/ML to identify and implement innovative solutions.

Communication : Translate complex technical concepts into clear, actionable insights for technical and non-technical audiences alike.

Required Qualifications :

- 10+ years of experience in data architecture, engineering, or enterprise data management roles.

- Demonstrated success leading large-scale data initiatives in life sciences or other highly regulated industries.

- Deep expertise in modern data architecture paradigms such as Data Lakehouse, Data Mesh, or Data Fabric.

- Strong hands-on experience with cloud platforms like AWS, Azure, or Google Cloud Platform (GCP).

- Proficiency in data modeling, ETL/ELT frameworks, and enterprise integration patterns.

- Deep understanding of data governance, metadata management, master data management (MDM), and data quality practices.

- Experience with tools and platforms including but not limited to :

1. Data Integration : Informatica, Talend

2. Data Governance : Collibra

3. Modeling/Transformation : dbt

4. Cloud Platforms : Snowflake, Databricks

- Excellent problem-solving skills with the ability to translate business requirements into scalable data solutions.

- Exceptional communication skills and experience engaging with both executive stakeholders and engineering teams.

Preferred Qualifications (Nice to Have) :

- Experience with AI/ML data pipelines or real-time streaming architectures.

- Certifications in cloud technologies (e.g., AWS Certified Solutions Architect, Azure Data Engineer).

- Familiarity with regulatory frameworks such as GxP, HIPAA, or GDPR.