You will be part of an innovative fast-growing Ag-Fintech company, whose mission is to revolutionize agricultural finance through data science and machine learning. You will be part of a dynamic and experienced team, contributing to data ingestion into our database, transformation pipelines, and ensuring periodic updates of this information. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.

Your responsibilities will mainly include, but will not be limited to, the following:

• Assemble and process large, complex data sets that meet business and product requirements
• Identify, design, and implement internal process improvements: automating manual processes and optimizing data delivery as well re-designing infrastructure for greater scalability
• Create and maintain scalable, test driven data pipeline architecture
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python and AWS tools.
• Work with data and analytics experts to strive for greater functionality in our data systems

Required qualifications & skills:

• Degree in Computer Science or related quantitative field, or substantial experience in data engineering at scale
• Enthusiastic, flexible team player who loves to dive in and “figure it out”
• Experience building data models, infrastructure, and ELT pipelines for reporting, analytics and data science.
• Experience in data technologies such as Spark, Python, Scala and SQL
• Experience in cloud computing, version control and development tools
• Experience with streaming ELT/ETL pipelines is preferred
• Ability to work independently and in a team environment, in a fast-paced agile environment
• Ability to identify systemic operational issues and resolve them.
• 3+ years of relevant experience
• English language proficiency

Preferred qualifications:

• Previous experience in working in big data environments such as Databricks or similar technologies.
• Previous experience in streaming data
• Previous experience in cloud infrastructure in the AWS stack

Attendance Requirements:

Traive is currently a hybrid workplace in terms of office attendance, namely all employees are required to attend the office a minimum number of days, while they may work the rest outside the office. The attendance policy may change from time to time depending on the safety requirements and precautions due to the pandemic, or other considerations.