Axiom Path
Be Part Of A High-Performing Team
This organization operates within the financial services sector, delivering data-driven solutions that support enterprise-scale decision-making. The technology team is composed of experienced engineers and analysts working collaboratively to build secure, scalable, and high-quality data platforms. The environment values technical excellence, documentation, and thoughtful problem-solving while supporting complex analytical and operational initiatives.
What’s In Store For You
This role offers the opportunity to contribute to large-scale data initiatives within a modern cloud-based environment. Team members gain exposure to advanced data technologies, collaborate closely with cross-functional partners, and work in a hybrid model that supports balance and productivity.
How You Will Make an Impact
Design and implement scalable, secure data solutions supporting analytics and reporting
Build and maintain robust ETL and ELT pipelines for batch and real-time data
Develop optimized data models and schemas for performance and reliability
Partner with analysts and business stakeholders to translate requirements into technical solutions
Improve data workflow efficiency, cost management, and system reliability
Participate in architectural decisions and engineering best practices
Create comprehensive technical documentation and contribute to code reviews
Are You an Experienced Data Engineering Professional Ready to Make an Impact?
5+ years of experience in software development using Python
Strong expertise in SQL and database technologies, including relational systems
Hands-on experience with data pipeline frameworks such as Apache Spark, Airflow, or Kafka
Solid understanding of data modeling, ETL/ELT processes, and performance optimization
Experience working in cloud-based data environments, preferably on Google Cloud Platform
Bachelor’s degree in Computer Science, Engineering, or a related discipline
Strong analytical thinking and the ability to communicate technical concepts clearly
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