Senior Data Engineer

Blankfactor is dedicated to engineering impact, building high-quality tech solutions for companies in fast-moving industries. They are seeking a Senior Data Engineer to help scale and modernize data environments within the embedded finance and payments space, transforming raw data into high-value insights while ensuring data integrity and platform reliability.

Responsibilities:

• Ingest and manage large-scale data architecture across AWS-based data stores including S3, Glue, Athena, and LakeFormation
• Interface with cross-functional technology teams to extract, transform, and load (ETL) data from a wide variety of transactional and analytical data sources using SQL and AWS big data technologies
• Continually improve, automate, and simplify ongoing data ingestion, engineering, reporting, and analysis processes to enable scalable, self-service support for business partners
• Partner closely with portal, operations, risk, and finance engineering teams to recognize and drive the adoption of data best practices, focusing heavily on data integrity/quality, robust pipeline analysis, rigorous validation, and documentation
• Act as a technical mentor to fellow team members, championing a culture of continuous learning and high engineering standards
• Create and optimize schemas and data models that align with complex business logic

Requirements:

• 5+ years of dedicated data engineering experience
• Proven expertise in Python (Spark) based ETL design, implementation, and production maintenance
• Strong proficiency with Python, JavaScript, and Pandas
• Deep hands-on experience designing and implementing infrastructure with: AWS S3, Glue, Athena, QuickSight, LakeFormation, and Lambda
• AWS CLI, SDK, and IAM
• Advanced expertise in schema design, data modeling, and writing highly optimized, complex SQL queries
• Familiarity working with either Apache Spark, Presto, Hudi, Hive, Hadoop, MapReduce, or similar MPP systems
• Highly motivated, open-minded problem solver with a passion for tackling tough technical challenges
• Exceptional communication and collaboration skills; a true team player with a positive, proactive mindset
• Strong educational foundation (Bachelor's or Master's degree in Computer Science, Information Systems, or an equivalent combination of education, training, and work experience)
• Direct experience working within the payments, billing, or financial services domain is highly advantageous
• Some exposure or foundational experience with Machine Learning workflows (e.g., AWS SageMaker) is a major plus