Core Competencies:
- Ethics. Works with integrity; Upholds organizational values
- Dependability. Follows instructions, and responds to management direction; results oriented and committed to achieving objectives and tasks as required
- Teamwork and Collaboration. Exhibits objectivity and openness to other’s views; Gives and welcomes feedback; Contributes to building a positive culture. Communicates effectively
- Professionalism. tactfully approaches others; Reacts well under pressure; Treats others with respect and consideration; Accountable for all actions and decisions
- Organizational Support. Follows policies and procedures; Completes administrative tasks correctly and on time; Supports organization’s goals and values
- Quality Management. Looks for ways to improve and promote quality; Demonstrates accuracy and thoroughness
- Decision Making. Analyzes each situation, looking for opportunities to make any situation more beneficial for the company. Participates effectively in communication to achieve optimum results
Job Overview:
Seeking a highly experienced Tech Lead / Senior Architect – Data Engineering to drive the design and implementation of enterprise-grade data platforms for a global engagement. This role will focus on building scalable, secure, and compliant data solutions to support advanced analytics, clinical insights, and business intelligence.
Key Responsibilities:
- Lead the end-to-end architecture, design, and implementation of scalable data platforms using Snowflake.
- Define and enforce data architecture standards, including modeling, naming conventions, and best practices.
- Design and implement robust ETL/ELT pipelines using DBT and cloud-native tools.
- Collaborate with global stakeholders (business, analytics, clinical, and IT teams) to translate requirements into scalable solutions.
- Drive data governance, lineage, cataloging, and quality frameworks across the platform.
- Ensure compliance with European data regulations (e.g., GDPR) and pharma-specific standards.
- Implement CI/CD pipelines and DataOps practices for automated testing, deployment, and monitoring of data workflows.
- Optimize Snowflake performance, including query tuning, clustering, and cost management.
- Provide technical leadership, architectural guidance, and mentorship to engineering teams.
- Evaluate emerging tools and technologies to continuously improve the data ecosystem.
- Work closely with DevOps and infrastructure teams to ensure high availability, scalability, and security.
Requirements:
- Strong hands-on expertise in Snowflake (data warehousing, performance tuning, security, cost optimization).
- Deep understanding of data warehousing concepts (dimensional modeling, star/snowflake schemas).
- Advanced proficiency in SQL and complex query optimization.
- Extensive experience in ETL/ELT development, especially with DBT.
- Experience in data architecture and distributed data systems design.
- Strong exposure to CI/CD pipelines (Git, Jenkins, GitHub Actions, Azure DevOps).
- Experience working with cloud platforms (AWS).
- Must have skills: Data Engineering/Architect with Snowflake, AWS, dbt, Python and SQL, Data Mesh.
Preferred Skills
- Experience with orchestration tools like Apache Airflow or similar.
- Exposure to data lake / lakehouse architectures.
- Experience with data visualization tools (Tableau, Power BI).
- Prior experience in the pharmaceutical / healthcare domain (clinical, R&D, or commercial data).