(SENIOR) DATA ENGINEER (M/F/D)

at  Philip Morris International

• Full-time in Vienna as soon as possible -
  Become part of a revolutionary change! We have decided to do something incredible. We’re transforming our business towards a smoke-free future and it’s not just about establishing a strong brand - the excitement is about building something new, innovative and unprecedented.
  Big changes bring big opportunities: wherever you join us, at Philip Morris Austria you’ll be given the freedom to work on new and innovative solutions and to advance your career in very different directions. Become part of our vision and join our Data Intelligence Team in Vienna.

THE “DATA INTELLIGENCE” TEAM:

We are looking for a “(Senior) Data Engineer” to join our “Data Intelligence” team based in our headquarter in Vienna, Austria. The team is building analytics capabilities to enable data driven decision making with focus on delivering high quality data for different business functions. The Data warehouse platform currently hosted on AWS and levering the Microsoft Business Intelligence stack will be moved to Snowflake and Matillion.

THE “DATA ENGINEER” ROLE:

As a “(Senior) Data Engineer”, you will join a growing team where you maintain and further enhance our Data warehouse using AWS services (S3 etc.), Terraform, Microsoft Services (SSIS, ETL, SQL etc.). You will also need good business understanding and communication skills for the day-to-day work with internal business functions, central expert teams, and vendors.
One of the key projects will be to lead the migration towards a global Enterprise Data Platform (Data Ocean) and leveraging tools such as Snowflake, Matillion and AWS.

YOUR RESPONSIBILITIES:

• Creating, Testing and Deploying Pipelines: Design, develop, and maintain data pipelines for efficient data ingestion, processing, and delivery.
• Ensure Data Completeness and Quality: Implement mechanisms to ensure data completeness, accuracy, and consistency across all data sources and processes.
• Optimizing and Maintaining Warehouse: Continuously improve the performance and scalability of the data warehouse, implementing optimization techniques and best practices.
• Continuous Improvement: Identify opportunities for process optimization and automation, striving for continuous improvement in data management practices.
• Data Analysis: Analyze and interpret data to provide actionable insights and recommendations to stakeholders, supporting data-driven decision-making processes.
• Work with Vendors: Collaborate with external vendors to integrate new data sources into the data ecosystem, ensuring seamless data flow and integration.
• Problem-Solving: Leveraging innovative approaches to optimize processes and enhance data quality.
• Proactive Role: Actively anticipate and resolve potential data issues before they escalate, demonstrating a proactive approach to data.