Data Engineer

At Rayn, we don’t just work—we innovate, collaborate, and create solutions that leave a lasting impact. As part of our team, you’ll have the opportunity to shape the future of a purpose-driven organization that is redefining how technology can address societal & public health challenges.

Rayn is seeking a highly skilled and experienced Data Engineer to design, build, and optimize our data infrastructure and pipelines. This pivotal role will be responsible for ensuring the availability, reliability, scalability, and efficiency of our data systems, enabling data-driven decision-making and supporting advanced analytics and reporting. The ideal candidate will possess deep expertise in data warehousing, ETL/ELT processes, big data technologies, and a strong commitment to data quality and governance.

What you will bring to Rayn as a Data Engineer: 

As a Data Engineer at Rayn, your role is crucial in shaping our data infrastructure and analytics capabilities. You will:

• Identify and assess source datasets available in the customer’s global data lake for ingestion into the platform.
• Map and align new datasets with the existing local data lake structure to maintain a consistent data format and schema.
• Implement data ingestion pipelines across the lakehouse architecture layers (Bronze, Silver, and Gold).
• Integrate newly ingested data into the existing data model, including Dimension and Fact tables within the current star schema architecture.
• Replicate and adapt existing KPI calculation logic by redirecting established processing pipelines to the newly ingested datasets.
• Develop output datasets and data products to deliver newly calculated KPIs to the relevant Business Units (BUs) using existing delivery processes.
• Develop data validation logic and data quality checks using PySpark within Databricks to ensure accuracy and reliability of ingested data.
• Integrate, process, transform, and cleanse datasets originating from multiple legacy systems.

Development Tools:

• Databricks
• PySpark
• Azure Data Factory
• Synapse
• Azure Data Lake (Gen2)
• Azure data explorer
• Azure data studio
  

Your qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 1-3 years of relevant experience in data engineering, with a strong portfolio of designing and implementing data solutions.
• Expertise in big data technologies (Apache Spark, DBT), cloud platforms  (Azure, GCP), and data development in data lake/delta lake architectures.
• Proficiency in programming language SQL, and infrastructure as code technologies (Terraform, Helm charts for Kubernetes).
• Expert knowledge of Kubernetes, object storages (S3, Azure Data Lake Store)
• Strong problem-solving skills, excellent communication abilities, and the capacity to thrive in a fast-paced environment.