Description:
We are looking for a highly motivated and highly potential Senior Staff Engineer to join our Data team to make big business impacts and grow your career.
This is an exciting time to be part of the Data team. We offer sophisticated business solutions that empower diverse customers. The data generated from these systems, applications, and platforms is rich and complex. As one of the most valuable assets of ours, this data holds immense potential to drive value for our customers and the business.
Experience you’ll bring
- Bachelor's degree in Computer Science, Software Engineering, or a related field, OR demonstrable equivalent deep understanding, experience, and capability. A Master’s or PhD degree in Computer Science (or related field) is a plus.
- 10+ years of experience in large-scale software engineering.
- A technically deep, innovative, empathetic, and passionate technical leader capable of delivering on business needs.
- Strong problem-solving skills, with excellent communication and collaboration abilities.
- Highly self-motivated and eager to learn, consistently adopting new technologies to improve productivity and the quality of deliverables. Proficient in leveraging GenAI technologies to enhance work productivity and build innovative products/systems for customers.
- Extensive experience in architecture design, creating simple, high-quality, performant, and efficient solutions for large, complex problems.
- Deep expertise in CI/CD automation.
- Rich experience in combined engineering practices and Agile development, with a track record of leading teams to adopt these methods effectively.
- Extensive experience and strong implementation skills in programming languages such as Java, C#, Golang, and Python, including coding, automated testing, measurement, and monitoring, ensuring high productivity.
- Expertise in data processing techniques, including data pipeline/platform development, SQL, and database management.
- Extensive experience in data ingestion, cleaning, processing, enrichment, storage, and serving, using tools such as ELT, SQL, relational algebra, and databases.
Preferred Qualifications:
- Proven expertise in designing and implementing scalable, reliable, and cost-effective data architectures, including data lakes, lake houses, and data warehouses, to support analytics, real-time processing, and AI/ML applications.
- Extensive experience building and optimizing high-throughput data ingestion frameworks for diverse data types (structured and unstructured) using tools like Kafka, Spark, AWS Glue, and Apache NiFi, with strong ETL/ELT proficiency.
- Hands-on experience with AWS, Azure, or GCP managed services for data storage, compute, and orchestration, along with Infrastructure as Code (IaC) for scalable provisioning.
- Expertise in efficient data modeling and schema design for analytical and transactional data, focusing on optimal data retrieval and storage practices.
- Deep knowledge of event-driven and streaming architectures to enable real-time data processing and responsive data products.