Data Engineer II

As a Data Engineer II at Nium, your primary responsibilities will include designing and implementing scalable data pipelines, collaborating with cross-functional teams to understand data requirements, developing ETL processes for data accuracy, and optimizing data storage solutions. You'll also be involved in data modeling and generating insightful reports that guide business decisions and driving machine learning solutions across the organization.

To apply for the Data Engineer II position at Nium, you should have a Bachelor’s degree in Computer Science, Engineering, or a related field, along with 1-3 years of experience in data engineering. Strong programming skills in SQL and Python are essential, as well as familiarity with big data technologies like Hadoop, Spark, Kafka, and Flink. Experience with building machine learning models is also desirable.

The Data Engineer II role at Nium requires strong programming skills in SQL and Python. Proficiency in these languages is necessary to design and build effective data solutions, automate ETL processes, and conduct data analysis. Familiarity with big data technologies may require additional languages depending on specific projects.

Nium places a strong emphasis on employee wellness, offering comprehensive medical coverage, an employee assistance program available 24/7, and generous vacation policies, including a year-end shutdown. The company promotes a flexible hybrid working environment, allowing team members to balance work life and personal wellness effectively.

As a Data Engineer II at Nium, you can expect to work on innovative projects involving the design and implementation of high-performance data pipelines, developing ETL processes, optimizing data storage solutions, and driving the adoption of machine learning capabilities across various payment processing systems.

In my previous roles, I designed and maintained ETL processes to ensure data accuracy and completeness. I often utilized SQL for data extraction and transformation while using tools like Apache Kafka for real-time data processing. I focus on optimizing these processes to handle large datasets efficiently, which aligns with Nium's commitment to scalable solutions.

I have hands-on experience with several big data technologies including Hadoop for distributed storage, and Spark for fast processing. I've utilized Kafka for real-time data streaming and Flink for building data processing pipelines. My experience with these tools equips me to contribute effectively as a Data Engineer II at Nium.

To ensure data quality and governance, I implement data validation checks at each stage of the ETL process. This includes detailing data profiles, conducting audits, and adhering to best practices for data governance. By setting policies that prioritize data security and integrity, I can help maintain the high standards expected at Nium.

In my last position, I developed a machine learning model to predict churn rates among customers. Starting with data preprocessing, I utilized Python libraries like Pandas and Scikit-learn to build and validate the model. This experience aligns well with Nium’s goal of enhancing payment processing through innovative machine learning solutions.

My approach to problem-solving in data engineering is analytical and systematic. I begin by breaking down the problem into manageable components, conducting thorough data analysis to identify root causes, and exploring potential solutions. This structured method allows me to effectively address challenges while ensuring that implemented solutions align with Nium’s infrastructure.

Data engineering plays a critical role in payment processing environments, facilitating the smooth transfer and analysis of large datasets. At Nium, effective data pipelines and infrastructure ensure timely access to accurate data, which is essential for making strategic business decisions, improving operational efficiency, and driving innovation across financial services.

In data engineering projects, I prioritize tasks based on their impact on project deadlines and overall team objectives. I typically conduct regular meetings with stakeholders to align on priorities, estimate efforts required, and adjust timelines based on the complexity of tasks. This ensures that critical milestones are met in alignment with Nium’s goals.

While working on a data project, I collaborated closely with marketing and sales teams to understand their data needs. By engaging in regular discussions and translating technical details into user-friendly terms, I effectively gathered requirements that informed our data architecture, ensuring that our solutions supported their objectives at Nium.

I have worked in cloud environments, particularly with AWS and Azure, to manage both data storage and processing functionalities. This experience allows me to leverage cloud technologies for scalable data solutions, which is essential for Nium's global operations and aligns well with modern data engineering practices.

I'm excited about the Data Engineer II role at Nium because of the opportunity to work on cutting-edge data infrastructure in a fast-paced fintech industry. I'm passionate about harnessing data to drive insights and innovations in payment solutions. I truly believe in Nium’s mission and am eager to contribute to a company that values both data and employee growth.