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Artificial Intelligence • Hardware • Information Technology • Machine Learning
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Artificial Intelligence • Hardware • Information Technology • Machine Learning
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Own and evolve a large-scale shared data platform supporting billion-row workloads. Design open-lakehouse foundations, batch and streaming ingestion, CDC, platform APIs, orchestration, metadata, governance, observability, and data-quality capabilities. Drive production reliability, incident response, performance, cost optimization, capacity planning, and recovery improvements. The role requires hands-on distributed-systems engineering, architecture leadership, coding, deployment, and operational ownership at SDE-3 or Staff level.
This role is for one of Weekday’s clients
Min Experience: 7+ years
Location: India
JobType: full-time
We are looking for a hands-on Platform Engineer – Data (SDE-3 / Staff) to take ownership of a large-scale, billion-row shared data platform and help scale it from its current state to the next level of reliability, performance, and usability.
This is a data platform engineering role, not a business ETL or analytics-pipeline delivery position. You will design, build, and operate the foundational systems that product and engineering teams rely on. The role requires strong distributed-systems expertise, production engineering skills, and the ability to drive architecture while remaining deeply involved in coding and operations.
RequirementsWhat You’ll Own
- Build and evolve open-lakehouse foundations using technologies such as Apache Iceberg, Delta Lake, or Apache Hudi, including table lifecycle management, partitioning, data layout, compaction, schema evolution, catalog management, and query operations.
- Design and operate batch and streaming ingestion systems, including CDC, data contracts, deduplication, checkpointing, replay, recovery, and failure handling.
- Develop platform services, APIs, and self-service capabilities that enable engineering and product teams to consume and manage data independently without creating unnecessary dependencies on a central platform team.
- Build and manage orchestration and workload execution systems across Kubernetes and workflow technologies such as Prefect, Argo, or Airflow.
- Establish robust metadata, lineage, governance, data quality, and observability capabilities across the platform.
- Own production reliability and operational excellence, including incident response, SLAs, data freshness, performance and cost optimization, capacity planning, and recovery improvements.
- Establish engineering standards and architectural patterns that enable the platform to scale across teams and workloads.
- Typically 7+ years of software or platform engineering experience, with demonstrated SDE-3 / Staff-level ownership and impact, regardless of current job title.
- Proven, hands-on experience owning a shared data platform in production, rather than exclusively building pipelines or applications on top of an existing platform.
- Strong expertise in distributed-systems design and production-grade software development using one or more of Python, Java, Go, or Scala.
- Meaningful experience across batch processing, streaming, data ingestion/CDC, storage and query systems, and platform operations.
- Demonstrated ability to improve reliability, scalability, performance, cost efficiency, or developer self-service in large-scale production environments.
- Strong individual contributor who can influence architecture, establish technical standards, and drive complex engineering initiatives while remaining close to the code and operational details.
- Comfortable taking end-to-end ownership, from architecture and implementation through deployment, monitoring, incident response, and continuous improvement.
Experience with open-source or production-scale implementations involving:
- Apache Iceberg, Apache Hudi, or Delta Lake
- Apache Kafka, Apache Flink, or Debezium
- Apache Spark, Trino, or Pinot
- Kubernetes and cloud-native workload platforms
- Data catalogs, metadata platforms, lineage systems, or governance frameworks
- Data quality and observability platforms
This role is not intended for candidates whose experience is primarily focused on:
- BI or reporting
- Analytics engineering
- Data warehouse modeling
- Business-facing ETL development only
- Generic backend engineering without significant data-platform ownership
- Assembly and configuration of managed services without deep platform engineering ownership
- Narrow ownership of a single infrastructure or data component
- People-management-focused roles without substantial hands-on engineering involvement
- Data Platform
- Distributed Systems
- Apache Iceberg
- Apache Hudi
- Delta Lake
SDE-3 / Staff Engineer
Experience: Typically 7+ years
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