Serko
Website:
serkotech.com
Company:
https://www.linkedin.com/company/serko-ltd
Seniority: Mid-Senior level
Industries: Software Development
Job details:
About the job
Serko is a cutting-edge Travel Technology platform in global business travel & expense technology. When you join Serko, you become part of a team of passionate travelers and technologists bringing people together, using the world’s leading business travel marketplace. We are proud to be an equal opportunity employer, we embrace the richness of diversity, showing up authentically to create a positive impact. There's an exciting road ahead of us, where travel needs real, impactful change.
With offices in New Zealand, Australia, North America, and China, we are thrilled to be expanding our global footprint, landing our new hub in Bengaluru, India. With rapid a growth plan in place for India, we’re hiring people from different backgrounds, experiences, abilities, and perspectives to help us build a world-class team and AI powered Travel ecommerce product.
As a Staff Engineer
Key responsibilities
Platform architecture
- Own the end-to-end architecture of the data platform — ingestion, storage, transformation, orchestration, and serving — and evolve it as the business scales.
- Architect scalable, secure, high-performance data systems across cloud environments (Azure, AWS, GCP), including event-driven and distributed designs.
- Lead build-versus-buy and technology selection decisions for core platform components, and author the design documentation that supports them.
Pipeline engineering
- Design and operate reliable, high-throughput batch and real-time pipelines processing [X TB/day] across [N] source systems.
- Define and enforce data modeling standards (dimensional, Data Vault, or medallion architecture) so that analytics and ML teams work from trusted, well-documented datasets.
- Lead initiatives across data segregation, de-duplication, cleanup, persistence, and lifecycle management.
Governance, quality, and security
- Establish data quality, lineage, and observability practices, including SLAs, producer–consumer data contracts, and incident response for data issues.
- Implement and maintain data security controls: encryption standards, access control mechanisms, and compliance with applicable regulations.
Reliability and cost
- Optimize compute and storage for both performance and cost; own the platform's unit economics.
- Act as the escalation point for the platform's most complex production incidents.
Technical leadership
- Mentor senior and mid-level engineers through design review, pairing, and code review.
- Translate architectural direction into implementation guidance teams can execute against.
Required qualifications
- 8+ years in software or data engineering, including at least 5 years focused on large-scale data systems.
- Expert-level SQL (including T-SQL) with strong query optimization skills, and proficiency in Python, Java, or Scala.
- Production experience with distributed processing frameworks (Spark, Flink, or equivalent).
- Hands-on experience with a modern cloud data warehouse or lakehouse (Snowflake, BigQuery, Databricks, Redshift) and open table formats (Iceberg, Delta Lake, Hudi).
- Strong command of data modeling, metadata management, and data cataloguing tools.
- Demonstrated ability to architect large-scale distributed systems, including event-driven architectures (e.g., Kafka), distributed transactions, and reasoned trade-offs between availability and consistency.
- Experience implementing data security protocols, encryption standards, and access control mechanisms.
- Experience with orchestration frameworks (Airflow, Dagster, Prefect) and infrastructure-as-code (Terraform).
- A track record of architecture you owned that others adopted — in production, at scale, under real constraints.
- Clear technical writing and the ability to make a technical case to both engineers and executives.
Preferred qualifications
- Streaming infrastructure at scale (Kafka, Kinesis, Pulsar) and change-data-capture patterns (Debezium).
- Familiarity with data governance and compliance regimes ([GDPR / HIPAA / SOC 2 / DPDP Act]).
- Experience leading a platform migration or major re-architecture.
- Open-source contributions to data tooling.
Good to have Java and Spring Boot expertise combined. However, Java is mandatory.
This role builds and operates JVM services alongside the data platform. The following depth is expected:
- System Design & Architecture: Proven ability to architect large-scale distributed systems. Demonstrated expertise in building data-intensive, event-driven architectures (using tools like Kafka) and making educated tradeoffs regarding databases and infrastructure. Knowledge of distributed transactions and the ability to decide between availability versus consistency when building scalable solutions.
- Java & Collections: Deep expertise in core Java, JVM internals, multithreading, and a masterful understanding of the Java Collections Framework (knowing the internal workings, space/time complexities, and selection tradeoffs).
- Spring & Spring Boot: Solid foundational knowledge of the Spring ecosystem, including a clear understanding of Spring Core (IoC, Dependency Injection, AOP, Security) and the building blocks of Spring Boot applications.
Cloud-native service engineering
- Design and deployment of high-performance APIs and microservices for cloud environments.
- Systems engineered for horizontal scaling, with high availability, fault tolerance, and graceful degradation under heavy load.
- Ongoing evaluation and tuning of deployed services for efficiency, reliability, and operational cost.
Click on Apply to know more.
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