Data Engineer

Summary: The role of Data Engineer involves designing and implementing scalable data pipelines, developing high-quality data products, and collaborating with cross-functional teams in Zürich. The position requires a strong background in data engineering, including experience with Big Data technologies and cloud platforms. The engineer will also be responsible for governance, security, and driving innovation in data practices. This is a contract position aimed at enhancing the organization's data strategy and compliance standards.

Key Responsibilities:

• Data Pipeline Leadership: Design and implement scalable data pipelines for both real-time and batch processing. Make strategic architectural decisions to support long-term FAIR-compliant data products.
• Data Product Development: Build high-quality, compliant data products. Tackle complex data challenges and contribute to shaping the overall data strategy.
• Cross-Functional Collaboration: Work closely with domain experts and cross-functional teams to model data landscapes, acquire data extracts, and define secure data exchange methods.
• Data Integration & Processing: Ingest and transform data from various sources into Big Data platforms (e.g., Snowflake). Develop ERDs and reusable pipelines for advanced analytics use cases.
• Governance & Mentorship: Support the Data Mesh Engineering Collective by establishing governance standards, ensuring regulatory compliance, and mentoring team members.
• Security & Infrastructure: Ensure alignment with information security standards. Collaborate with infrastructure teams to define tailored tech stacks and make strategic decisions on data architecture.
• Innovation & Best Practices: Drive innovation in data engineering, define quality standards, and actively share knowledge and best practices across teams.
• Technical Excellence: Stay current with modern data engineering tools and platforms (e.g., Ataccama, Monte Carlo) and contribute to enterprise-wide tooling and standards.

Key Skills:

• Master's degree in Computer Science, Data Engineering, or a related field.
• 5+ years of experience in data engineering, including leading and mentoring teams.
• Proven expertise in designing and scaling large data systems and pipelines.
• Strong programming skills in Python, Java, SQL, or Scala.
• Experience with Big Data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, GCP).
• Deep understanding of data security and compliance requirements.
• Skilled in working with structured, semi-structured, and unstructured data.
• Familiarity with data modeling, ETL tools, Git, and CI/CD pipelines.
• Strong testing and monitoring practices for data reliability and quality.
• Excellent communication skills and experience in client-facing roles.
• Strong organizational and interpersonal skills, with the ability to work independently and collaboratively.

Salary (Rate): undetermined

City: Zürich

Country: Switzerland

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

We have a current opportunity for a Data Engineer on a contract basis. The position will be based in Zürich. For further information about this position please apply.

Key Responsibilities
* Data Pipeline Leadership: Design and implement scalable data pipelines for both real-time and batch processing. Make strategic architectural decisions to support long-term FAIR-compliant data products.
* Data Product Development: Build high-quality, compliant data products. Tackle complex data challenges and contribute to shaping the overall data strategy.
* Cross-Functional Collaboration: Work closely with domain experts and cross-functional teams to model data landscapes, acquire data extracts, and define secure data exchange methods.
* Data Integration & Processing: Ingest and transform data from various sources into Big Data platforms (e.g., Snowflake). Develop ERDs and reusable pipelines for advanced analytics use cases.
* Governance & Mentorship: Support the Data Mesh Engineering Collective by establishing governance standards, ensuring regulatory compliance, and mentoring team members.
* Security & Infrastructure: Ensure alignment with information security standards. Collaborate with infrastructure teams to define tailored tech stacks and make strategic decisions on data architecture.
* Innovation & Best Practices: Drive innovation in data engineering, define quality standards, and actively share knowledge and best practices across teams.
* Technical Excellence: Stay current with modern data engineering tools and platforms (e.g., Ataccama, Monte Carlo) and contribute to enterprise-wide tooling and standards.

Required Qualifications
* Master's degree in Computer Science, Data Engineering, or a related field.
* 5+ years of experience in data engineering, including leading and mentoring teams.
* Proven expertise in designing and scaling large data systems and pipelines.
* Strong programming skills in Python, Java, SQL, or Scala.
* Experience with Big Data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, GCP).
* Deep understanding of data security and compliance requirements.
* Skilled in working with structured, semi-structured, and unstructured data.
* Familiarity with data modeling, ETL tools, Git, and CI/CD pipelines.
* Strong testing and monitoring practices for data reliability and quality.
* Excellent communication skills and experience in client-facing roles.
* Strong organizational and interpersonal skills, with the ability to work independently and collaboratively.

Preferred Qualifications
* 3+ years of experience in the pharmaceutical or healthcare sector.
* Experience with REST APIs and integrating data from diverse sources.
* Knowledge of regulatory frameworks (e.g., GMP, FDA) and quality systems.
* Familiarity with AI/ML solutions and platforms (e.g., Dataiku).
* Understanding of software engineering best practices (e.g., code reviews, maintainability).

SThree_Germany is acting as an Employment Business in relation to this vacancy.