High Salary) Data Engineer Graph

Job Description

- Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions
- Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks
- Develop and maintain semantic 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 multi-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 standard processes 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 comprehensive 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. T

Basic Qualifications and Experience:

- Doctorate Degree OR Masters degree with 2- 4years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR
- Bachelors degree with 4- 6years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR
- Diploma with 7- 9 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field

Preferred Qualifications and Experience:

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

Functional Skills:

Must-Have Skills:

- Proficiency in SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasks
- Hands on experience with data technologies and platforms, such as Databricks, 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
- Experience with system administration skills, such as managing Linux and Windows servers, configuring network infrastructure, and automating tasks with shell scripting. Examples include setting up and maintaining virtual machines, troubleshooting server issues, and ensuring data security through regular updates and backups.
- Solid understanding of data modeling, data warehousing, and data integration concepts
- Solid experience using RDBMS (e.g. Oracle, MySQL, SQL server, PostgreSQL)
- 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 user documentation in Confluence
- Understanding of data governance frameworks, tools, and standard processes

Professional Certifications:

- Databricks Certified Data Engineer Professional preferred

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

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