Middle Data Engineer

RESPONSIBILITIES:

• 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.

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:

• 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.
• Proficiency in English at a B2 level.