On a daily basis you will:
- Closely support stakeholders in making data-driven decisions.
- Work with different InPost departments and business lines.
- Gather requirements, harness large-scale, real-time data from various sources, analyze it and, prepare insights and recommendation about business critical areas and processes.
- Design, develop, and extend our data model layers that support optimized and scalable calculations and visualizations of successful analytics outcomes.
- Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale data environment. Maintain and advocate for these standards through code reviews.
- Collaborate with cross-functional teams including Data Engineers, Data Scientists, and Business Analysts to deliver integrated data solutions.
- Prototype and coordinate data visualizations.
Which skills should you bring to the pitch:
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Min 3 years of experience in an analytical role handling vast volumes of data in (preferably in domains such as Marketing, Logistics, Customer or Sales).
- Experience in data modeling and implementing complex data-driven solutions is a strong plus.
- Strong proficiency in Python/PySpark for data analysis, SQL for data processing, Bash scripting to manage Git repositories.
- Proven ability to pull insightful and actionable conclusions from complex data and communicate recommendations to business stakeholders clearly and concisely.
- Comprehensive understanding of the technical aspects of data warehousing, including dimensional data modeling and ETL/ELT processes.
- Ability to translate business needs into data models.
- Strong understanding of real-time data: ability to request and handle data from both backend and frontend systems, including internal and external platforms.
- Self-motivated and self-managing, with the ability to work independently and mange multiple tasks simultenously.
- Strong interpersonal skills with the ability to collaborate effectively with cross-functional teams
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Fluency in English: verbal and written.
It would be awesome if you have:
- Experience in working with Apache Spark in Databricks.
- Familiarity with cloud-based data platforms (e.g. GCP, Azure, AWS).
- Familiarity with modern data building tools like Apache Airflow, DBT.
- Familiarity with data visualization tools such as PowerBI/Tableau/Looker.
- Knowledge of data governance principles and practices.
- Ability to thrive in a highly agile, intensely iterative environment.
