Senior Analytics Engineer

Company Description

InPost Group is an innovative European out-of-home deliveries company, revolutionizing the way parcels are delivered to customers. With operations across several countries, our network of intelligent lockers (Paczkomat®) provides customers with a fast, convenient, and secure delivery option. Our mission is to provide best-in-class user experience for merchants and consumers. “Simplify everything” – redefining e-commerce logistics. We work by innovating the market with constant technological research and with meticulous attention to the customer.

The Data & AI department is seeking a Senior Analytics Engineer to join our Core Team. In this role, you’ll shape analytical standards and implement innovative solutions, impacting our operations across Poland and 7 international markets. Remote work is possible.

Daily you’ll work with: Apache Spark in Databricks, Databricks various features, Python/PySpark, SQL, Kafka, Power BI, GitLab, Google BigQuery, inhouse data modeling tool.

Job Description

On a daily basis you will:

• Drive innovation and improvements by evaluating new tools (e.g., Data Quality monitoring) and platform features (e.g., Genie Space on Databricks).
• Monitor the effectiveness of solutions by tracking implemented actions (e.g., naming convention adherence, metadata completeness, MR quality).
• Define workflows and coding standards for style, maintainability, and best practices on the analytical platform.
• Evangelize platform users on the best practices for its use and encouraging teams to continuously improve their working methods. Advocate for coding standards through various workshops and guidelines.
• Monitor the market for new tools and methodologies in data product development area.
• While the role involves conceptual work, you’ll also have opportunities for hands-on coding, such as analyzing AI readiness and implementing AI solutions to automate data development tasks.
• Work with various Data&AI competencies (Data Consultants, Data Engineers, AI Engineers, Cloud Engineers, Data Architect)

Qualifications

Which skills should you bring to the pitch:

• At least 5 years of experience in an analytical role working with large datasets
• Experience in data modeling and implementing complex data-driven solutions is a strong plus
• Excellent proficiency in Python/PySpark for data analysis, SQL for data processing, bash scripting to manage Git repositories
• Comprehensive understanding of the technical aspects of data warehousing, including dimensional data modeling and ETL/ELT processes
• Experience with real-time data processing and the ability to handle data from various backend/frontend systems.
• Familiarity with cloud-based data platforms (GCP/Azure/AWS)
• The ability to present technical concepts and solutions to diverse audiences
• Self-motivated with the ability to work independently and manage multiple tasks
• Excellent interpersonal skills with the ability to collaborate effectively with cross-functional teams
• Fluent in English: verbal and written

Nice to have:

• Experience in working with Apache Spark in Databricks
• 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
• Positive and solution-oriented mindset

Additional Information

The course of the recruitment process:

1. HR Interview
2. Devskiller test
3. Technical Interview (60 min)
4. Home task
5. Home task presentation and discussion (60 min)