Data Engineer

About the Role

Join a dynamic team at an Engineering company as a Data Engineer, where you will have the opportunity to shape the organization's data landscape. With a team of passionate professionals, you will directly influence critical business decisions by transforming raw data into actionable insights. This role offers significant growth potential, enabling you to broaden your technical expertise and advance your career in a fast-paced environment.

Responsibilities

• Take ownership of the end-to-end data structuring processes within the organization.
• Transform large volumes of raw, unstructured, and semi-structured data into standardized datasets fit for analysis.
• Support various business functions by providing structured datasets for risk analytics and fraud detection.
• Develop and maintain data pipelines and automated processes to ensure efficient data flow.
• Collaborate with cross-functional teams to understand data requirements and provide analytical support.
• Continuously enhance SMS parsing capabilities to expand coverage and improve data quality.
• Monitor and troubleshoot data-related issues to ensure system performance and reliability.

Requirements

• A minimum of 3 years of experience in Data Engineering, Analytics Engineering, or similar roles within the fintech domain.
• Proven ability in SMS parsing and transforming raw customer data into actionable financial signals.
• Experience establishing a continuous learning cycle to improve parser coverage.
• Strong proficiency in both Python and SQL at a production level.
• Demonstrated experience in handling unstructured data sources such as logs, JSON, and APIs.
• Proven skills in database design and data modeling for efficient data storage and retrieval.
• A track record of building data pipelines, schedulers, and automated cron jobs.
• Ability to thrive in a startup culture characterized by high ownership and initiative.

Nice to Have

• +Familiarity with modern data platforms such as AWS, Snowflake, or Google BigQuery.
• +Experience with data warehousing solutions like Redshift.
• +Understanding of algorithms and best practices in data engineering.