Job Description
Senior Data Engineer (Singapore)
SpringCube is searching for an experienced and driven Senior Data Engineer to lead the data engineering efforts of a cutting-edge FinTech company revolutionizing the lending industry in Southeast Asia. Backed by renowned VCs, this forward-thinking organization is on a mission to revolutionize the lending experience through cutting-edge technology, data-driven decision-making, and personalized financial solutions. This is your opportunity to spearhead the development of a next-generation data infrastructure that will shape the future of lending.
What You’ll Do:
- Take the helm in designing and implementing highly scalable and reliable data pipelines for batch and real-time processing of lending data, ensuring seamless data flow and accessibility.
- Architect and build a robust data infrastructure that supports data ingestion, storage, processing, and retrieval at scale, accommodating the company’s rapid growth and evolving needs.
- Establish and champion data quality standards and best practices across the organization, fostering a culture of data integrity and accuracy.
- Mentor and guide junior data engineers, nurturing their talent and fostering their professional growth within the team.
- Collaborate effectively with data scientists, analysts, and business stakeholders, understanding their data requirements and delivering efficient data solutions.
- Proactively identify and address performance bottlenecks and scalability challenges in the data platform, ensuring optimal performance and efficiency.
- Continuously research and evaluate new data engineering technologies and tools, driving innovation and improvement within the data infrastructure.
- Play an active role in fostering a strong data-driven culture within the company, advocating for data-informed decision-making at all levels.
What You’ll Need:
- 7+ years of experience as a Data Engineer, with at least 3 years in a senior or lead role, preferably within the FinTech industry, specifically lending or a related domain.
- Demonstrated expertise in architecting and building large-scale data platforms, showcasing your ability to design and implement complex data solutions.
- Deep understanding of data warehousing, data modeling, and ETL processes, enabling you to design efficient and effective data pipelines.
- Mastery of SQL and experience with a variety of database technologies (relational and NoSQL), ensuring adaptability and expertise in managing diverse data.
- Extensive experience with Big Data technologies (e.g., Hadoop, Spark, Hive, Kafka), enabling you to handle and process massive datasets with ease.
- Proficiency in cloud-based data platforms (e.g., AWS, GCP, Azure) and infrastructure-as-code tools (e.g., Terraform), allowing you to leverage the power and scalability of the cloud.
- Strong programming skills in Python or Java, enabling you to develop custom solutions and automate tasks efficiently.
- Experience with data pipeline orchestration tools (e.g., Airflow, Prefect), ensuring seamless and efficient execution of complex data workflows.
- Exceptional communication, leadership, and mentoring skills, enabling you to guide and inspire your team while effectively collaborating with stakeholders.
Bonus Points:
- Experience with stream processing technologies (e.g., Flink, Kinesis) for real-time data analysis.
- Experience with data governance and data security best practices, ensuring data compliance and protection.
- In-depth knowledge of financial data and regulations, particularly those relevant to the lending industry.
- Contributions to open-source data engineering projects, demonstrating your passion for the field and commitment to community development.
To Apply:
Register your profile on SpringCube and apply for this position through the platform. All applications will be treated in the strictest confidence.
