Engineer Jobs

About The Position

Requirements

• Degree in Computer Science, Engineering or Management of Information Systems
• 0 - 1 year of experience and/or exposure to data modelling (star and/or snowflake schema) and data engineering using Azure cloud system.
• Experience using Databricks to write data transformation scripts
• Experience designing data pipelines for data movement between Azure and Databricks cloud systems
• Experience with relational database design, methods for efficiently retrieving data, as well as data preparation/wrangling both on demand and in an industrialized way
• Gather and process raw data at scale (including writing automation scripts, calling APIs, write SQL queries, SharePoint extraction etc.)
• Experience with programming in Python, pySpark and/or Scala with a demonstrated capability for code modularization, knowledge of DRY/WET programming concepts, code refactoring to optimize efficiency and data preprocessing using native or custom modules

Nice To Haves

• Strong analytical and problem-solving skills.
• Excellent interpersonal and communication skills with the ability to build positive relationships.
• Engaging and personable, with a customer-focused and collaborative approach.
• Ability to collaborate effectively with cross-functional teams and manage multiple tasks and projects simultaneously in a fast-paced environment.

Responsibilities

• Clean, prepare, and optimize data for analytics and visualization.
• Design, build, and integrate data from multiple sources.
• Manage complex queries to ensure data accessibility and functionality.
• Work with Data Engineers, Solution Architects, and Product Owners to embed models and design scalable solutions.
• Support product lifecycle activities, including stakeholder management and continuous improvement.
• Combine advanced analytics techniques with traditional data engineering practices.
• Streamline and standardize data workflows for improved efficiency.
• Build automated data pipelines to reduce manual effort and enhance integration.
• Design scalable infrastructure to support growing data volumes and user needs.
• Implement monitoring systems and optimize data operations for performance.
• Apply agile methodologies for timely delivery of data solutions.
• Foster a culture of continuous improvement and innovation.
• Maintain clear documentation and promote knowledge sharing.
• Define performance metrics and reporting mechanisms to measure and communicate operational success.

Benefits

• Flexible and hybrid work arrangements
• Excellent training and development programs as well as opportunities to grow within the company
• Access to the Discount Company store with Nestlé, Nespresso, and Purina products (Located across various Nestle offices/sites)
• Additional discounts on a variety of products and services offered by our preferred vendors and partnerships