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backend developer - data platform
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what will you do?
  • apply fundamental principles to solve technological problems efficiently
  • design and build robust, scalable components of CRED's open-source-first data platform — focusing on ingestion, reconciliation, observability, and cost-aware compute using Spark on EKS and Delta/Iceberg lakes
  • engineer high-throughput, low-latency data ingestion systems across RDS, Kafka, DynamoDB, and more — powering 100+ TB of daily data flows across regulated domains (PCI, PII)
  • abstract complexity for data producers and consumers by building internal SDKs, self-serve orchestration, and smart developer tooling
  • lead the design and rollout of AI copilots for data engineers and analysts — including pipeline assistants, quality bots, and lineage-aware query editors
  • instrument observability, lineage, and access control as first-class features in the platform — ensuring auditable and secure multi-tenant usage across subsidiaries
  • collaborate with product, infra, compliance, and data science teams to deliver platform capabilities that accelerate internal builds while enforcing governance
  • drive open-source adoption by replacing legacy SaaS or monoliths with modular, community-aligned infrastructure
  • continuously profile and optimize infrastructure for petabytes of data scale and cost efficiency 
  • stay informed about evolving technologies and best practices in data engineering, contributing to the enhancement of data processes
  • communicate effectively with internal and external stakeholders, providing updates on the progress of key initiatives
  • represent the organization in the tech community, building a strong brand presence
you should apply if you :
  • have 5+ years of experience building large-scale distributed data systems with a strong grasp of Spark, Iceberg/Delta Lake, and orchestration frameworks (Airflow, Dagster, or similar)
  • prefer building platforms over pipelines — and enjoy solving challenges in multi-tenant architecture, developer experience, lineage, and cost attribution
  • have hands-on experience deploying open-source data frameworks on cloud-native environments like EKS or EMR, and automating deployments via IaC or CI/CD
  • have worked on systems where data quality, auditability, and compliance are critical — and have engineered observability into your platforms
  • are comfortable writing production-grade Python, Scala, or Java, and can design SDKs or frameworks to simplify engineering workflows
  • have a product mindset: you think of internal developers as customers and optimize for their velocity, safety, and trust
  • are excited by the potential of AI-augmented platforms — copilots for query suggestions, smart catalogs, lineage tools, and anomaly detection bots
  • thrive in ambiguous environments and want to define the architecture and tooling that powers a lot of engineers,analysts,operation and product folks
  • believe in open source, modularity, and solving infra problems for 10x scale
  • familiarity with SQL, basic database management systems, and an understanding of data warehousing concepts
  • effective communication skills, both written and verbal, with the ability to convey technical concepts to non-technical stakeholders
  • an ability to work independently and as part of a collaborative team in a dynamic environment
  • eagerness to learn and adapt, with an interest in data streaming technologies

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