Sr Associate Data Engineer

Role overview

Roles and responsibilities

• Design, develop, and maintain solutions for data generation, collection, and processing.
• Assist with data pipeline design and development.
• Create ETL pipelines and ensure data quality when migrating and deploying data across systems.
• Create metric dashboards, self-service analytics, and business insights.
• Maintain data models, data dictionaries, and documentation.
• Use cloud platforms, with AWS preferred, to build scalable data solutions.
• Follow coding, testing, and reusable component best practices.
• Perform exploratory data analysis, business analysis, and feature engineering.
• Support product review documents, regulatory inspections, and process documentation.
• Assess data quality, cleanse data, and perform data analytics with data engineers.

Basic qualifications

• 5–8 years of experience in computer science, IT, or a related field with a master's degree, bachelor's degree, or diploma.
• Hands-on experience with big data platforms such as Databricks, PySpark, and SparkSQL.
• Experience with workflow orchestration and performance tuning for big data processing.
• Hands-on experience with Python or R packages for exploratory analysis, feature engineering, and machine learning training.
• Proficiency in SQL, data analysis tools, and data visualization platforms.
• Excellent problem-solving skills with large, complex datasets.

Functional and professional skills

• ETL, data modeling, data warehousing, and data integration experience are advantageous.
• Interest in GenAI or LLM technology and natural-language data products is advantageous.
• Strong critical thinking, communication, collaboration, presentation, and teamwork skills.
• A Certified Data & Analytics professional certification is listed.