Data Engineer

Level 4 Data Engineer:

What you will do

Let’s do this. Let’s change the world. In this vital role you will be responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and performing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has deep technical skills, experience with database technologies, and a deep understanding of data architecture and ETL processes. 

Roles & Responsibilities:

• Design, develop, and maintain data solutions for data generation, collection, and processing 

• Be a crucial team member that assists in design and development of the data pipeline 

• Build data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems 

• Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions 

• Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform. 

• Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks 

• Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs 

• Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency 

• Implement data security and privacy measures to protect sensitive data 

• Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions 

• Collaborate and communicate effectively with product teams 

• Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast-paced business needs across geographic regions 

• Identify and resolve complex data-related challenges 

• Adhere to best practices for coding, testing, and designing reusable code/component 

• Explore new tools and technologies that will help to improve ETL platform performance 

• Participate in sprint planning meetings and provide estimations on technical implementation 

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. 

Basic Qualifications:

• Master’s/ Bachelor's degree and 5 - 9 years of Computer Science, IT or related field experience 

Preferred Qualifications:

Must-Have Skills:

• Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing 

• Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools 

• Excellent problem-solving skills and the ability to work with large, complex datasets 

• Solid understanding of data governance frameworks, tools, and best practices. 

• Knowledge of data protection regulations and compliance requirements 

Good-to-Have Skills:

• Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development 

• Good understanding of data modeling, data warehousing, and data integration concepts 

• Knowledge of Python/R, Databricks, SageMaker, cloud data platforms 

• Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform. 

Professional Certifications

• Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments) 

Soft Skills:

• Excellent critical-thinking and problem-solving skills 

• Good communication and collaboration skills 

• Demonstrated awareness of how to function in a team setting 

• Demonstrated presentation skills