Design, develop, and maintain data pipelines using Apache Airflow
Develop and optimize Python scripts, APIs, and SQL queries for efficient data processing
Build and improve ETL workflows for data extraction, transformation, and loading
Contribute to data warehouse evolution and data architecture improvements
Collaborate with business stakeholders to translate business needs into technical solutions
Identify opportunities to automate and optimize data-related processes
Monitor, maintain, and improve the stability and performance of data pipelines
Analyze datasets to identify trends, anomalies, and opportunities for operational improvement
Deliver reliable, accessible, and user-friendly data solutions to end-users
Ensure data consistency, quality, and availability across systems
Support incident resolution and continuous improvement initiatives
Work closely with cross-functional teams in an Agile environment

At least 5 years of experience in data engineering, analytics, or data platform environments
API development in Python
Proficiency in Python, PySpark, SQL and Oracle Database
Experience in data warehousing environments
Apache Airflow pipeline development
Git and Agile methodologies
Strong analytical and problem-solving mindset
Excellent communication and synthesis skills
Adaptability and proactive attitude
Client-focused approach

Data Analytics Engineer

Key skills