Data Warehouse Design: Develop and implement data warehouse structures that are scalable, efficient, and aligned with business needs.
Data Pipeline Creation: Architect, build, and oversee scalable ETL workflows to gather, transform, and store extensive data from varied sources.
Database Oversight: Enhance and manage SQL databases to ensure optimal data storage, retrieval, and system performance.
Data Integration: Consolidate data from different sources, ensuring its quality, consistency, and accessibility.
Automation and Scripting: Utilize Python and PySpark to streamline and automate data processing tasks and workflows.
Team Collaboration: Engage with stakeholders to grasp their data requirements and deliver effective data solutions.
Performance Enhancement: Evaluate and refine data workflows and queries to achieve peak performance and efficiency.
Process Documentation: Create and keep detailed records of data engineering practices, system architectures, and workflows.
Issue Resolution: Address and resolve data-related issues to maintain data accuracy and reliability.
What we offer:
OPPORTUNITIES:
Excellent working environment: the company is big enough to be reliable, yet small enough to be person-oriented.
Full-cycle projects and product development.
Training & development-focused approach: clear roadmap for training employees to sustain and enhance the productivity of the organization as a whole, internal technical meetups, free English classes.
Collaboration with the teams from the European Union and United States both on-site and remotely.
Work-life balance to suit everyone: flexible working hours, loyal sick-leave policy, student-exam-session-friendly approach, corporate events and sport activities.
Requirements:
REQUIREMENTS:
Skilled in crafting and fine-tuning complex SQL queries and managing relational databases.
Proficient in Python for data manipulation and automation, with experience using libraries like Pandas and NumPy.
Cloud platform knowledge, preferably AWS, AWS Certifications would be a huge benefit.
Understanding Git CI/CD.
Experienced in DWH design and architecture, including schema development, data modeling, and performance optimization
Knowledgeable about cloud-based data warehousing platforms (e.g., AWS Redshift, Google BigQuery, Snowflake).
Strong analytical and problem-solving capabilities.
Effective communicator with the ability to work collaboratively across teams.
