Are you passionate about designing and building scalable data solutions that empower businesses to make data-driven decisions? We’re looking for a Senior Data Engineer to join our team and lead the development of advanced data systems in a growing and dynamic environment.
● Design, build, implement, and maintain data warehouses and self-service business intelligence solutions.
● Develop scalable, efficient ETL/ELT processes and optimize SQL for seamless data flows.
● Create and manage robust data pipelines, ensuring reliability, accuracy, and performance.
● Collaborate with cross-functional teams to define and implement datasets for various use cases, including batch-based analytics and real-time streaming.
● Troubleshoot performance bottlenecks in data pipelines and warehouses, implementing solutions to enhance efficiency.
● Apply modern best practices for data quality, lineage, governance, and cleaning to maintain optimal pipeline performance.
● Lead the adoption and integration of data tools and frameworks such as Airflow, Snowflake, Docker, GitLab CI, Kafka, AWS, GoodData, or alternatives.
● Mentor junior engineers and collaborate as part of agile development teams to deliver frequent and confident releases.
Requirements:
● Experience: At least 6 years of proven experience in Data Engineering, with expertise in building and optimizing large-scale data solutions.
● Technical Proficiency:
○ Strong SQL skills and extensive experience with ETL/ELT processes.
○ Proficiency in one or more analytical programming languages such as Python.
○ Hands-on experience with modern data tools and frameworks (e.g., Airflow, Snowflake, Docker, Kafka, AWS).
● Analytical Expertise: Understanding of common analytical practices, statistical methods, and dataset design for varied use cases.
● Best Practices: Deep knowledge of data pipeline design, data governance, lineage, and data quality management.
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