Sr. Data Engineer – Clinical Data Hub

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 design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions

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 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

Collaborate and communicate effectively with product teams

Master’s or Bachelor's degree with 8 - 12 years of experience in Computer Science, IT or related field

Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (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

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

Strong understanding of data governance frameworks, tools, and best practices.

Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)

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

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

Clinical development domain knowledge is a plus

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

Certified Data Scientist (preferred on Databricks or Cloud environments)

Machine Learning Certification (preferred on Databricks or Cloud environments)

SAFe for Teams certification (preferred)

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

This position requires you to work a later shift and may be assigned a second or third shift schedule.

Candidates must be willing and able to work during evening or night shifts, as required based on business requirements.