Data and Analytics Engineer

Job Description:

Experience Level: Level 4 (advanced): 7-15 years

What you’ll do in the role:

This role will involve hands‑on development, data pipeline creation, and close collaboration with stakeholders across the organization. This role requires a self‑starter with strong execution skills and the ability to work independently. You will be expected to not only execute on the current strategy but also contribute to its evolution. We value diversity of thought and are committed to building a team that reflects the diversity of our global community Data and Analytics Engineering.

This position that provides specialist data analysis and expertise that drive decision‑making and business insights as well as crafting data pipelines, implementing data models, optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI‑based techniques.

What you’ll bring to the role:

• Experience being a practitioner in data engineering or a related field.
• Design and implement data pipelines and workflows to support analytics and reporting needs.
• Develop interactive dashboards and reports using visualization tools like Power BI and Tableau.
• Collaborate with business stakeholders to understand requirements and translate them into data models and visualizations.
• Utilize Dataiku and other analytics platforms for data preparation, machine learning workflows, and advanced analytics.
• Ensure data quality, integrity, and security across all analytics solutions.
• Optimize performance of dashboards and queries for large datasets.
• Stay updated on emerging trends in data analytics and visualization technologies.
• Experience working on Snowflake and Databricks (Min one of the two).
• Knowledge of database systems (SQL and NoSQL).
• Experience on Snowflake Cortex will be really appreciated.
• Familiarity with cloud platforms (AWS, Azure) and their data services.
• Experience using Jupyter notebooks for data exploration, analysis, and visualization.
• Excellent communication and collaboration skills.
• Ability to work independently and as part of a geographically distributed team.

Good to have Skills:

• Familiarity with programming skills in Python.
• Experience with data warehousing concepts and technologies.
• Familiarity with data governance and security best practices (e.g., data access control, data masking).
• Experience with Agile methodologies.
• Familiarity with data catalog and metadata management tools (e.g., Collibra).
• Familiarity with CI/CD pipelines and DevOps practices.

Personal skills:

• Integrity and ownership, good team player.
• Ability to work under time and resource dependencies and constraints.
• Ability to find simple and effective solutions.
• High degree of motivation to expand technical and business knowledge.