Analytics Engineer - Industrial Business Data Platform

Position: Analytics Engineer - Industrial Business Data Platform
Location: Madrid
Experience: Between 2 and 4 years of experience

• Design and maintain data pipelines from SAP, Excel, APIs, and other sources.
• Work with technologies such as ClickHouse, Snowflake, and relational databases.
• Create curated layers and reusable data models for dashboards, reporting, and internal applications.
• Improve data quality, consistency, and traceability.
• Optimize queries and the performance of data models and structures.
• Design aggregate tables, materialized views, and indexes when they add value to performance and scalability.
• Create quality controls and data validations.
• Document models, definitions, and key metrics.
• Collaborate with business areas to translate functional needs into robust and sustainable data models.

INSUD PHARMA operates across the entire pharmaceutical value chain, providing specialized knowledge and expertise in scientific research, development, manufacturing, sale, and marketing of a wide range of active pharmaceutical ingredients (API), finished dosage forms (FDF), and branded pharmaceutical products, adding value to human and animal health.

INSUD PHARMA's activity is organized into three synergistic business areas: Industrial (Chemo) and Branded (Exeltis), with more than 9,000 professionals in over 50 countries, 20 state-of-the-art facilities, 15 specialized R&D centers, 12 commercial offices, and more than 35 pharmaceutical subsidiaries, serving 1,150 customers in 96 countries worldwide. At INSUD PHARMA, we believe in innovation and sustainable development.

We are looking for an Analytics Engineer for our Industrial Business Data Platform, with a technical profile and business vision, capable of building a solid, reliable, and scalable data layer for Supply Chain, connecting source systems and creating reusable models for analytics, reporting, and internal applications.

This will be a key position for transforming business needs into robust, usable, and scalable data solutions.

To succeed in this position, we are looking for professionals who bring:

• Between 2 and 4 years of experience in positions related to data analytics, data engineering, or analytics engineering.
• Education in Engineering, Computer Science, Mathematics, Statistics, or similar disciplines.
• Advanced SQL knowledge.
• Experience with Python.
• Experience working with ClickHouse, Snowflake, and PostgreSQL.
• Knowledge of data extraction from SAP.
• Proficiency in Excel and Power Query.
• Experience in ETL / ELT processes.
• Knowledge of Git, Docker, and API consumption/integration.
• Knowledge of dimensional modeling.

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