MTS 1, Software Engineer, Data

At eBay, we're more than a global ecommerce leader — we're changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We're committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

Cloud Data Technologies (CDT) team at eBay is responsible for all the data engineers of end-to-end data lifecycle for all eBay data from onsite to analytics use cases. We are seeking someone passionate about data-driven technologies and architectures.

We're seeking a Member of Technical Staff 1 (Software Engineer) who can work independently and is an expert in big data technologies. The primary role is to build and maintain the systems that allow a company to collect, store, and analyze data at scale. Their work is the foundation for all data-driven activities, including decision support and data science.

• Designing & Building Data Pipelines: Creating systems (often called ETL or ELT pipelines) that automatically extract data from various sources (like databases, APIs, and log files), transform it into a usable format, and load it into a central repository.
• Managing and optimizing large-scale data storage solutions, such as data warehouses (for structured data) and data lakes (for raw, unstructured data).
• Support platform capabilities across ingestion, streaming, lakehouse/warehouse, catalog, and governance.
• Data Modeling: Designing the structure of data to make it efficient for analysts and data scientists to query..
• Ensuring Data Quality & Governance: Implementing checks and processes to ensure data is accurate, consistent, reliable, and secure.
• Optimizing Performance: Tuning data pipelines and database queries to ensure they run quickly and efficiently, even with massive volumes of data.
• Collaboration: Working closely with data scientists, data analysts, and business stakeholders to understand their data needs and provide them with the right data in the right format.

Must-haves

• 8+ years of professional software engineering experience (or equivalent impact)..
• Expert-Level SQL: You must be able to write complex, efficient SQL queries to retrieve, manipulate, and transform data.
• Strong coding skills in Java/Python and familiarity with CI/CD.
• Hands-on with some of: Kafka/Flink, Spark, Delta/Iceberg, Kubernetes, NoSQL/columnar stores.
• Proven ability to work independently, make sound tradeoffs, and deliver quality outcomes with minimal supervision.
• Solid debugging, performance analysis, and system design skills.

Database Knowledge: Deep understanding of different database types:

• Relational Databases (SQL): (e.g., PostgreSQL, MySQL)
• NoSQL Databases: (e.g., MongoDB, Cassandra) for unstructured data.

Data Pipeline & Orchestration Tools:

• Apache Airflow: The industry standard for scheduling, automating, and monitoring data pipelines.

Qualifications

• Education: A Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics, or a related technical field. A Master's degree is a plus.

• Impact at scale: Your platform work powers analytics and ML across a global marketplace.
• Hard problems: Streaming freshness/correctness, storage/compute efficiency, multi-region resiliency.
• Collaborative culture: Inclusive team that values autonomy, craftsmanship, and knowledge sharing.

Growth: Strong mentorship, career development resources, and sustainable on-call practices.

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