IT Enterprise Analytics Specialist

About this role

A leading global pharmaceutical company is seeking an experienced Data Engineer / BI Engineer to design, build, and maintain scalable data platforms that enable analytics, reporting, and data-driven decision making. The role focuses on data ingestion, transformation, modeling, and analytics enablement, with strong emphasis on Python-based data engineering and modern data architectures.

Responsibilities

• Data Engineering & Data Architecture:
• Design and maintain scalable data pipelines for ingesting, transforming, and serving structured and semi-structured data.
• Develop robust data transformation and processing logic using Python and distributed data processing frameworks.
• Design and maintain analytical data models (dimensional models, fact/dimension tables) optimized for reporting and analytics.
• Ensure data quality, reliability, performance, and consistency across the data platform.
• Translate business and analytical requirements into efficient and maintainable data solutions.
• Analytics & BI Enablement:
• Build and maintain semantic / analytical models that support enterprise reporting and self-service analytics.
• Collaborate with analysts and business users to deliver trusted datasets and metrics.
• Support reporting and dashboarding solutions by providing optimized data structures and calculations.
• Delivery & Collaboration:
• Produce clear technical documentation including data models, transformation logic, and pipeline designs.
• Collaborate with cross-functional teams including data analysts, data engineers, and business stakeholders.

Requirements

• Bachelor’s degree in data science, computer science, data engineering, or a relevant field.
• 1-3 years of BI development experience.
• 3+ years of cloud-based BI development experience
• Excellent English language verbal and written communication.
• Able to analyse and understand complex data.
• Able to implement modules that have security and authorization frameworks.

- Strong problem-solving skills

• Technical

Skills

• Programming & Data Processing:
• Strong proficiency in Python for data engineering and analytics use cases.
• Experience building reusable, testable, and maintainable data transformation code.
• Data Warehousing & Modeling:
• Strong knowledge of SQL and analytical query optimization.
• Solid understanding of data warehousing concepts (ETL/ELT, fact and dimension modeling).
• Experience designing star and snowflake schemas for analytics and reporting.
• Understanding of semantic layers and metrics definitions for BI consumption.
• Cloud & Modern Data Platforms:
• Experience working with cloud-based data platforms and data lakes(Preferred Azure).
• Understanding of scalable data architectures (Lakehouse, warehouse, streaming vs batch).
• BI & Analytics:
• Experience supporting BI and reporting tools through well-designed datasets and models (Preferred Power BI).
• Knowledge of analytical calculations, KPIs, and performance optimization for reporting workloads.
• CI/CD & DevOps (Supporting Skills):
• Working knowledge of CI/CD concepts applied to data and analytics projects.
• Experience using version control systems (e.g., Git, Perforce or Apache Subversion) for managing data, code, and artifacts.
• Familiarity with deployment pipelines and environment promotion for data solutions