Data Engineer (#1062)

Описание

Your expertise:

• Strong analytical skills and a proven ability to extract actionable insights from data
• Experience with at least one SQL-based database or data warehouse solution (e.g., MySQL, PostgreSQL, MSSQL, Snowflake, BigQuery, or Apache Iceberg-based systems)
• Solid understanding of ETL processes and experience building them from scratch (experience with AWS Glue or Apache Airflow is a plus)
• Proficiency in Python
• Experience in gathering and analyzing system requirements
• Excellent communication skills
• Intermediate level of English (B1 or above)

Will definitely be a plus:

• Cloud experience, particularly with AWS
• Familiarity with BI tools such as Tableau, Power BI, or similar

What’s in it for you? 

• Opportunity to deal with top-notch technologies and approaches in a world-leader product company with millions of customers
• Opportunity to make a difference for online privacy, freedom of speech, and net neutrality
• Decent market rate compensation depending on experience and skills
• Developed corporate culture: no micromanagement, culture based on principles of truth, trust, and transparency
• Support of personal and professional development
  • coverage of costs of external trainings, conferences, professional literature
  • support of experienced colleagues
  • in-house events and trainings
  • regular knowledge sharing in teams
  • English classes and speaking clubs
• Life-balance support
  • 25 working days of vacation
  • 5 days of paid sick leave per year without providing a medical certificate (no limitation on sick leaves with medical confirmation)
  • generous maternity / paternity leave program
• Professionally strong environment, friendly and open atmosphere, ability to influence the product development and recognition for it

You will be involved into:

• Create sustainable analytics solutions for internal clients
• Learn new technologies 
• Creating and implementing tracking documents to meet stated requirements for metadata management, operational data stores and ETL environments
• Collaborate with internal customers and IT partners, including system architects, software developers, database administrators, design analysts and information modeling experts to determine project requirements and capabilities, and strategize development and implementation timelines
• Research new technologies, data modeling methods and information management systems to determine which ones should be incorporated into company data architectures, and develop implementation timelines and milestones