Sr. Associate Data Engineer

Roles & Responsibilities:

• Design, develop, and maintain data solutions for data generation, collection, and processing
• Be a key team member that assists in design and development of the data pipeline
• Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems
• Contribute to the creation of metric dashboards, self-serve analytics, and business insights using Tableau or Power BI
• Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency
• Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
• Adhere to best practices for coding, testing, and designing reusable code/component
• Exploratory data analysis, understand business knowledge, do feature engineering
• Support generation of annual product review documents, regulatory inspections, and process documentation
• Work with data engineers on data quality assessment, data cleansing and data analytics

Basic Qualifications and Experience:

• Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Engineering or equivalent).
• 5–8 years of work experience in Information Technology, Information Systems, or a related field
• Experience in the global pharmaceutical industry preferred.

Functional Skills:

Must-Have Skills

• Hands on experience with big data technologies and platforms, such as Databricks (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing
• Hands on experience with various Python/R packages for EDA, feature engineering and machine learning model training
• Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools
• Proficiency with data visualization platforms like Tableau, Power BI, or matplotlib/seaborn for Python
• Excellent problem-solving skills and the ability to work with large, complex datasets

Good-to-Have Skills:

• Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development
• Strong understanding of data modeling, data warehousing, and data integration concepts
• Interest in GenAI/LLM technology and building data products that support natural language interfaces

Professional Certifications:

• Certified Data & Analytics professional

Soft Skills:

• Excellent critical-thinking and problem-solving skills
• Strong communication and collaboration skills
• Demonstrated awareness of how to function in a team setting
• Demonstrated presentation skills

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