(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:

• Step 1: HR Interview

• Step 2: Devskiller test

• Step 3: Technical Interview (60 min)

• Step 4: Home task

• Step 5: Home task presentation and discussion (60 min)