トレンド企業

eBay
eBay

Buy, sell, and discover.

MTS 1, Software Engineer, Data Platforms

職種データエンジニアリング
経験ミドル級
勤務地Bengaluru, India
勤務オンサイト
雇用正社員
掲載2ヶ月前
応募する

福利厚生

401k

ストックオプション

育児休暇

必須スキル

Java

Python

Distributed Systems

System Design

At e Bay, 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.

About e Bay

e Bay is a global commerce leader that connects millions of buyers and sellers around the world. We empower people and create economic opportunities for individuals, businesses, and communities. We're driven by a vision to create a more sustainable form of commerce that benefits the environment and society as a whole. Join us as we continue to innovate and shape the future of e-commerce.

Job Description:

Cloud Data Technologies (CDT) team at e Bay is responsible for all the data infrastructure and management of end-to-end data lifecycle for all e Bay data from onsite to analytics use cases. We are seeking a Software Engineer passionate about data-driven technologies and architectures.

About the Role

We’re seeking a Member of Technical Staff 1 (Software Engineer) who can work independently and is an expert in distributed systems. You’ll design and deliver well-scoped services and features that advance e Bay’s Core Data Platform—improving scalability, reliability, and developer experience. This role is Data Platform Engineering (not data engineering): you’ll build and evolve the platform itself rather than author application pipelines.

What you’ll do and learn

  • Independently design, implement, and ship distributed services and features end-to-end (design → code → tests → deploy → operate).

  • Build core platform capabilities across ingestion, streaming, lakehouse/warehouse, catalog, and governance.

  • Write production-grade code with strong observability (metrics, logs, traces) and SLOs, and participate in on-call for the services you own.

  • Diagnose and resolve performance, scalability, and correctness issues in distributed environments.

  • Contribute design docs for your areas; participate in reviews to uphold reliability, security, and cost best practices.

  • Collaborate with product, infra, and analytics teams to align technical work with business outcomes.

What you bring

Must-haves

  • 6 years of professional software engineering experience (or equivalent impact).

  • Expertise in distributed systems fundamentals (consensus, replication, partitioning, consistency models, fault tolerance) and practical experience building and running such systems in production.

  • 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.

Nice-to-haves

  • Experience building multi-tenant platform services, data governance, or privacy-by-design controls.

  • Contributions to open-source distributed systems or data platforms.

What Success Looks Like (6–12 Months)

  • Consistently ships independent, well-scoped features/services to production with strong reliability.

  • Demonstrably improves throughput/latency/cost or availability/SLOs on owned services.

  • Becomes a go-to engineer for distributed-systems debugging and design conversations within the team.

  • Maintains high code quality, test coverage, and quality-in-release metrics.

Why Join CDT e Bay

  • 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.

Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.

eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talentebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.

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eBayについて

eBay

eBay

Public

eBay Inc. is an American multinational e-commerce company based in San Jose, California, that allows users to buy or view items via retail sales through online marketplaces and websites in 190 markets worldwide.

10,001+

従業員数

San Jose

本社所在地

$28.1B

企業価値

レビュー

10件のレビュー

3.8

10件のレビュー

ワークライフバランス

3.2

報酬

2.8

企業文化

4.1

キャリア

3.0

経営陣

2.7

72%

知人への推奨率

良い点

Supportive team culture and colleagues

Good benefits and health coverage

Flexible work arrangements

改善点

Management issues and lack of direction

Limited career advancement opportunities

Compensation below expectations

給与レンジ

2,735件のデータ

Mid/L4

Mid/L4 · BUSINESS ANALYTICS 3

3件のレポート

$166,000

年収総額

基本給

$134,381

ストック

-

ボーナス

-

$166,000

$166,000

面接レビュー

レビュー4件

難易度

3.0

/ 5

期間

14-28週間

体験

ポジティブ 0%

普通 75%

ネガティブ 25%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Interview

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience