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Job Description
The Scientific Data Product Line is responsible for enabling data for the Discovery, Preclinical, Translational Medicine (DPTM) and Developmental Sciences and Clinical Sciences (DSCS) organizations to get to better and faster insights in the drug discovery process.
Primary Responsibilities
Understand user problems and pain points. Design and develop solutions to address business needs using enterprise solutions
Lead data engineers on the team to ensure solution are fit for purpose and align to enterprise needs
Design, develop and maintain data pipelines to extract data from a variety of sources and populate data lake, data warehouse and Lakehouse
Develop the various data transformation rules and data modeling capabilities
Collaborate with Product Analyst, Data Scientists, Machine Learning Engineers to identify and transform data to make data understandable
Work with data governance team and implement data quality checks and maintain data catalogs
Use Orchestration, logging, and monitoring tools to build resilient pipelines
Use test driven development methodology when building ELT pipelines
Use Git for version control and understand various branching strategies
Work as part of an Agile team
Describes what to solve by writing problem statements and requirements and facilitates the “how” with the development team
Planning, designing, and conducting testing activities, and compiling critical content for training and communication for our users
Design and implement test cases
Create technical documentation as needed for SDLC
Partner with business and IT leadership to formulate business cases
Required Experience and Skills
B.Sc. or higher degree in Computer Science or Chemistry equivalent field required
Minimum 3-5 years working with customers to define requirements, preferably data
Domain knowledge - Pharmaceutical drug discovery and pre-clinical development
Hands-on experience with AWS services (S3, IAM, Redshift, SageMaker, Glue, Lambda, Step Functions, CloudWatch)
Experience with platforms like Databricks, Dataiku, Delta Lake
Experience with data governance, quality checks, and data catalog capabilities
Experience with data integration & transformation tools – AWS Glue, Starburst Trino, Databricks
Proficient in CI/CD using GitHub Actions, Jenkins, CloudFormation, Terraform, Git, Docker, Apache Airflow
Proficient in Python, Spark – PySpark
Demonstrates growth and product mindset. Ability to work in a cross functional team setup
Be able to work independently, anticipating and resolving problems
Excellent written and verbal communications skills
Effectively engage both technical and non-technical stakeholders and users
Preferred Experience and Skills
Any AWS developer or architect certification
Experience in Java
Experience with Matillion ETL for Data Transformation
Experience working in Agile software development
Familiarity with NoSQL Databases
Familiarity with ontologies and use of them to create data products
What we offer
Exciting work in a great team, global projects, international environment
Opportunity to learn and grow professionally within the company globally
Hybrid working model, flexible role pattern
Pension and health insurance contributions
Internal reward system plus referral programme
5 weeks annual leave, 5 sick days, 15 days of certified sick leave paid above statutory requirements annually, 40 paid hours annually for volunteering activities, 12 weeks of parental contribution
Cafeteria for tax free benefits according to your choice (meal vouchers, Lítačka, sport, culture, health, travel, etc.), Multisport Card
Vodafone, Raiffeisen Bank, Foodora, and Mall.cz discount programmes
Up-to-date laptop and iPhone
Parking in the garage, showers, refreshments, massage chairs, library, music corner
Competitive salary, incentive pay, and many more
Current Contingent Workers apply
*A job posting is effective until 11:59:59PM on the dayBEFOREthe listed job posting end date. Please ensure you apply to a job posting no later than the dayBEFOREthe job posting end date.
10/01/2024
A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.
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