Data Engineer
emagine
Project Details
Industry: Pharmaceuticals
Assignment Type: B2B
Project Length: 12 months (extendable)
Start Date: ASAP/1 month
Project Language: English
Project Description
As a Data Engineer, you will join the Data Harmonisation Layer (DHL) Agile team, a global platform focused on collecting and harmonizing data from various Operational Technology (OT) sources across production facilities. You will collaborate closely with Agile teams, business partners, and stakeholders to drive the development and improvement of Manufacturing Intelligence (MI) products.
Responsibilities
- Engage in software development activities, including writing, reviewing, refactoring, testing, and documenting the code base.
- Construct production-ready stable and scalable data pipelines to facilitate efficient data flow.
- Act as a trusted advisor, providing technical expertise on projects and collaborating with Agile teams to handle enabler work.
- Participate in Agile events such as Program Increment (PI) planning, system demos, and Inspect and Adapt (I&A) sessions.
- Contribute to the promotion of a culture of continuous improvement and innovation within the organization.
Requirements
- Hold a master’s degree in computer science, engineering, chemistry, biology, or other relevant fields.
- Demonstrate experience with data engineering principles, including data warehousing, batch processing, data streaming, data lakes, databases, and data modelling.
- Possess proficiency in building CI/CD pipelines and coding/scripting skills (Bash, Python, or similar).
- Have hands-on experience with AWS services such as Lambda, Glue, IAM, Kinesis, MKS, Step Functions, DMS, RDS, Managed Grafana, SNS, S3, CloudWatch, etc.
- Be familiar with Infrastructure as Code (IaC) for managing the cloud.
- Exhibit strong mathematical, statistical, and problem-solving skills.
We offer
- Long-term cooperation
- Transparently built relations based on trust and fair play
- Co-financed benefits: Medicover card, Multisport card
- Internal reference bonus
Expertise level
Work arrangement
Key skills
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