Associate Data Engineer - R&D Omics

Location: Prakāshamnagar

Roles & Responsibilities :
Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions
Contribute to data pipeline projects from inception to deployment, manage scope, timelines, and risks
Contribute to data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency
Optimize large datasets for query performance
Collaborate with global cross-functional teams including research scientists to understand data requirements and design solutions that meet business needs
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, Software Engineers and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
Identify and resolve 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
Maintain documentation of processes, systems, and solutions
What we expect of you We are all different, yet we all use our unique contributions to serve patients. The [vital attribute] professional we seek is a [type of person] with these qualifications.

Basic Qualifications:

Bachelor s degree with 2 to 6 years of Computer Science, IT or related field experience

Preferred Qualifications:

1+ years of experience in designing and supporting biopharma scientific research data analytics (software platforms)
Must-Have

Skills:

Proficiency in SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasks
Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, Spark

SQL), workflow orchestration, performance tuning on big data processing
Excellent problem-solving skills and the ability to work with large, complex datasets
Good-to-Have

Skills:

A passion for tackling complex challenges in drug discovery with technology and data
Solid understanding of data modeling, data warehousing, and data integration concepts
Solid experience using RDBMS (e. g. Oracle, MySQL, SQL server, Postgre

SQL)
Knowledge of cloud data platforms (AWS preferred)

Experience with data visualization tools (e. g. Dash, Plotly, Spotfire)

Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstorming
Experience writing and maintaining technical documentation in Confluence
Professional

Certifications:

Databricks Certified Data Engineer Professional preferred

Soft Skills:

Strong learning agility, ability to pick up new technologies used to support early drug discovery data analysis needs
Collaborative with good communication skills.
High degree of initiative and self-motivation.
Ability to handle multiple priorities successfully.
Team-oriented with a focus on achieving team goals.