Adecco’s Client is seeking a Data Engineer with expertise in designing and implementing scalable data solutions within the life sciences sector. The ideal candidate will have strong experience with Snowflake, Matillion, and dbt, while supporting data-driven initiatives for commercial and medical applications.
Key Responsibilities:
Collaborate with cross-functional teams (development leads, product owners, stakeholders) to understand and translate business and technical needs into effective data solutions.
Design, implement, and optimize data solutions in Snowflake/Matillion/dbt, ensuring high performance, security, and compliance with regulatory standards.
Develop and maintain a comprehensive data catalog and data lineage for commercial and medical affairs applications.
Prototype and test new data solutions, supporting the testing team in creating the best strategies for quality assurance.
Ensure architectural alignment with industry best practices, participating in design reviews and implementation checks.
Work within an Agile framework to establish data quality checks, process orchestrations, and automate routine tasks.
Lead root cause analysis activities and mitigate vulnerabilities to ensure system reliability.
Enforce technical standards and best practices, governing the architecture and implementation of project modules.
Qualifications:
4-5 years of data engineering experience with proven expertise in ETL, data modeling, and data warehouse development using Matillion and Snowflake.
Strong understanding of life sciences and pharmaceutical data including patient data, CRM call activity, and marketing analytics (web traffic, email campaigns, consent management).
Experience aggregating data from channel sales (SP/SD), 3PL data, and CRM platforms (Veeva, Salesforce ServiceCloud, HealthCloud).
Hands-on experience in Snowflake data warehousing, with SnowPro certification preferred.
Advanced proficiency in SQL, Matillion, dbt, and Python with experience in ELT optimization.
Experience working with cloud technologies such as AWS Lambda, S3, and policy management.
Ability to handle end-to-end ETL integration processes, ensuring accuracy in reports, dashboards, and data visualizations.
Expertise in defining and implementing data quality standards and training teams on best practices.
Strong background in working with Agile teams and effective communication skills for presenting technical concepts.
Why Join?
Be part of a leading data team.
Work in a dynamic, Agile environment with opportunities for growth and development.
Apply today to join a forward-thinking team and make a tangible impact in the data space within the life sciences sector.