Company Description
TP is a global digital business services company with both global scale and local presence. We support our communities, clients, and the environment through our advanced, digitally powered business services. TP partners with some of the world's best brands, helping them streamline their business operations in meaningful and sustainable ways.
Job description:
The Data Engineer is an analytics specialist in the business, focusing on the management of data from multiple sources and providing data-driven insights for relevant departments. Ensures that collected data is relevant and exhaustive and interprets the analytics results. Ensures that the data collected is relevant and exhaustive and interprets the results of the analysis. Is a data analyst who transforms data into information, information into insights and insights into business decisions. The Data Engineer supports Operation Data Analysis and Data Science teams, by building scalable and dynamic data structures, optimized towards dashboard development, data analysis and models creation and deployment.
Work Experience
- Mandatory: 3+ years of experience in data engineering, with a strong track record in designing and delivering complex data solutions.
- Mandatory (one of the following):
- Minimum 1 year of professional experience with Azure Data Factory or Databricks, including control/data flow development and auditing; or
- Minimum 1 year of hands-on experience building data infrastructure within cloud environments (e.g., ingestion accelerators, data quality frameworks).
- English Level B2
Technical Skills
- Mandatory (one of the following): Proficiency in Azure Data Factory or Databricks, demonstrated through experience in designing pipelines, implementing control/data flows, and auditing; or proven hands-on experience developing cloud-based data infrastructure solutions (e.g., ingestion accelerators, data quality frameworks).
- Mandatory: Strong command of SQL, PySpark, and Python for custom scripting, transformations, and advanced data engineering tasks.
- Mandatory: Solid understanding of SQL Server (T-SQL), including job scheduling, backup strategies, indexing, and maintenance.
- Mandatory: Experience with ETL processes, data pipelines, and data warehousing concepts.
- Mandatory: Familiarity with DevOps practices, CI/CD principles, and version control tools (e.g., Azure DevOps).
- Optional/Plus: Strong proficiency in MSSQL and SQL Server architecture (including OLAP cubes, indexing, and performance optimization).
- Optional/Plus: Exposure to contact centers, shared services environments, or international markets.
- Optional/Plus: Knowledge of Power BI.
Personal Attributes
- Demonstrated initiative, innovation mindset, and strong problem-solving skills.
