Informacje o stanowisku

We are seeking a seasoned Data Architect with extensive experience in designing and implementing robust data solutions. As a senior engineer, you will play a pivotal role in shaping the data architecture and engineering practices in a big retail company. You’ll collaborate with solution architects, product managers, and engineering teams to ensure seamless integration and accessibility of data while building scalable, high-performance data ecosystems.

Your tasks*

• Collaborate with solution architects and product managers to determine the most suitable data architecture
• Partner with software engineers and data product managers to understand data and reporting requirements and translate them into effective data architecture solutions
• Design and implement data structures, ETL pipelines, and integration solutions for collecting data from both internal and external systems
• Develop performant, reliable, and scalable data solutions using modern architecture concepts such as data mesh, data lake, and data lakehouse
• Ensure data quality by writing tests, performing code reviews, and debugging complex data pipelines
• Work closely with engineering teams to ensure seamless integration of data across various systems and platforms
• Implement data governance and data quality assurance practices, ensuring data integrity across the organization
• Assist product managers in developing conceptual and detailed data models and blueprints that enable the development of advanced data products
• Support the design and development of ETL processes using tools like Snowflake, and Airflow, and message brokers like RabbitMQ and SNS/SQS

Requirements:

• 7 years of experience in data architecture, data engineering, or a related role
• Expertise in data engineering, database design, and data warehousing concepts
• Knowledge of modern data architecture concepts, including data mesh, data virtualization, data lakes, and data lakehouses
• Proficiency with data integration and pipeline tools such as Snowflake and Airflow
• Strong knowledge of ETL processes and message brokers like RabbitMQ and SNS/SQS
• Advanced proficiency in SQL and Java
• Familiarity with cloud platforms, especially Azure Databricks and AWS
• Strong understanding of data governance and data quality assurance practices

Nice-to-have requirements

• Knowledge of Python
• Experience with event-based customer analytics

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