Data Engineer-Streaming Systems & Application

Data Engineer-Streaming Systems & Application

More than a mission, C2FO is a better financial system changing the way every business gains access to the working capital they need to thrive. At C2FO, everyone is an employee-owner which means we’re all invested in our work and team members. We’re a company of team players and self-starters finding new and innovative ways to get things done. If you’re excited to learn, grow and leave your mark on our fast-growing organization, C2FO may be the place for you.

About C2FO

Headquartered in Kansas City, USA, C2FO has more than 800 employees worldwide, with operations throughout North America, Europe, India, Asia Pacific, and Australia. C2FO is the world’s largest on-demand working capital platform. Our mission is to ensure every business has the capital needed to thrive and we have delivered more than $275 billion in funding to businesses since our founding. How do we do this? By providing fast, flexible and equitable access to low-cost capital through our easy-to-use platform.

We provide technology with a human touch, giving our customers the direct support they need and ensuring our team members have the tools, resources and work environment they need to deliver on our promise to customers. With the C2FO platform, businesses worldwide have more working capital to fuel their growth, create jobs and develop new products.

Benefits

At C2FO, we take care of our customers and our people – the vital human capital that helps our customers thrive. That’s why we offer a comprehensive benefits package, flexible work options for work/life balance, volunteer time off, and more. Learn more about our benefits here. https://www.c2fo.com/amer/us/en-us/about-us/careers

About the Message Bus team:

Our Message Bus Team is a dynamic group of talented engineers who thrive on embracing challenges, valuing continuous learning, and consistently delivering results. With a relentless focus on revolutionizing the way data flows through our systems, our team's expertise in Kafka, Spark, and other streaming technologies ensures the seamless processing of real-time data, driving transformative impact for businesses globally. We foster a culture of innovation and collaboration, pushing the boundaries of data engineering possibilities. Join our team and be part of the journey to shape the future of finance while making a meaningful impact on the global economy.

About the Data Engineer - Streaming Technologies Application:

We are looking for a Data Engineer with a focus on Kafka, Spark, Flink, and other streaming technologies to play a critical role in our data infrastructure and analytics initiatives. As a Data Engineer, you will be responsible for designing, developing, and maintaining our data pipeline and streaming platforms. Your expertise in Kafka, Flink, Spark, and other similar technologies, or willingness to learn on the job, will be instrumental in ensuring the smooth and efficient flow of real-time data across our systems.

Essential Duties:

• Design, develop, and deploy data pipelines and streaming platforms using Kafka, Flink, Spark, and other relevant technologies.
• Configure and stand-up streaming related infrastructure using containerization technologies (Docker, Helm, Kubernetes).
• Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and implement scalable solutions.
• Optimize data ingestion, processing, and delivery mechanisms for high throughput and low latency.
• Monitor and troubleshoot data pipelines, ensuring data quality and system reliability.
• Perform data modeling and schema design for efficient storage and retrieval of streaming data.
• Stay up to date with emerging trends and technologies in the data engineering and streaming space, making recommendations for continuous improvement.
• Participate in code reviews, documentation, and knowledge-sharing activities.

Basic Qualifications:

• Bachelor's or master’s degree in computer science, Engineering, or a related field.
• 1+ years of professional experience as a Data Engineer, with basic understanding of streaming technologies (e.g., Kafka) and distributed frameworks (e.g., Spark, Flink) or a strong willingness to learn these technologies at a fast pace on the job.
• 2+ years’ experience understanding distributed systems, event-driven architectures, and data streaming concepts.

Preferred Qualifications:

• Experience in designing, implementing, and managing data pipelines, including the ability to write code based on defined requirements, conduct thorough testing, and familiarity with technologies such as Kafka, Apache Flink, Apache Spark, or similar platforms would be a plus.
• Experience with data integration, ETL processes, and real-time data processing frameworks, obtained through professional work or education projects, would be valuable.
• Solid programming skills in languages such as Java, Scala, or Python.
• Familiarity with cloud platforms like AWS, Azure, or GCP.
• Excellent problem-solving and analytical abilities.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.
• Familiarity with big data frameworks like Hadoop, Hive, or Presto.
• Experience with containerization technologies (Docker, Helm, Kubernetes).
• Understanding of data governance and data security practices.

Commitment to Diversity and Inclusion. As an Equal Opportunity Employer, we not only value diversity and equality, but we also empower our team members to bring their authentic selves to work every day. Our goal is to create a workplace that reflects the communities we serve and our global, multicultural clients. We recognize the power of inclusion, emphasizing that each team member was chosen for their unique ability to contribute to the overall success of our mission.

We do not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment decisions are based on qualifications, merit, and business needs.

#LI-REMOTE