Analytics Engineer - PL

Description

We are passionate about technology, creativity, and challenges. If you enjoy challenges, continuous learning, and value personal connections, join us! \# We value diversity and believe it is essential for innovation and delivering value to our customers. All our positions are open to everyone, with or without disabilities, regardless of age, gender, sexual orientation, ethnicity, religion, or any other characteristic. If you identify with this role, come join our team! **WHAT ARE WE LOOKING FOR?** We are seeking a **Mid-Level Analytics Engineer**, who wants to work with us in a relaxed and dynamic environment with continuous learning while developing large-scale projects alongside major national and international clients. We seek a professional who acts as a bridge between data engineering, data analysis, and business units. Their primary responsibility is to translate business requirements into analytical models by transforming raw data into structured, clean, standardized, and reliable data for consumption by data analysts and business unit professionals. To achieve this, they must possess skills related to data engineering, as well as communication and management abilities. **WHAT WILL THIS PROFESSIONAL DO?** * Develop and maintain data ingestion pipelines, structuring them across transformation layers (bronze, silver, gold) on platforms such as Databricks, BigQuery, Snowflake, or Redshift * Work with Delta Lake and Unity Catalog within Databricks-based projects * Define and standardize business metrics jointly with the client’s product and analytics teams * Ensure data quality and reliability through automated testing and pipeline monitoring * Support building semantic layers enabling autonomous data usage by business teams * Contribute to technical documentation of delivered projects * Collaborate with product, business, and engineering teams to understand analytical needs **WHAT IS REQUIRED FOR THIS POSITION?** * Ability to communicate effectively with both technical and non-technical stakeholders * Organization and self-management skills * Knowledge and experience with SQL and dimensional modeling * Knowledge and experience with Python * Familiarity with cloud services (Azure, AWS, GCP) * Knowledge of Git for code versioning * Knowledge and experience with data visualization tools (Power BI, Looker, Tableau, etc.) **PROCESS STEPS:** * Application * Cultural fit interview * Technical interview * Client interview * Hiring