Lead Backend Engineer

Location: Noida, India

Department: PE-Cloud

Experience: 8+

Skills: Elasticsearch, solr, NEMSIS, Databricks, Python

• • Own the lifecycle of data attributes across the technology stack, from definition and modeling through ingestion, indexing, APIs and presentation.
  • Define scalable data models and attribute structures to support evolving healthcare data requirements.
  • Develop and maintain data ingestion and enrichment workflows using Python.
  • Work closely with Java/Spring services to expose and serve enriched data through APIs.
  • Collaborate with front-end teams to ensure data is effectively presented and consumed.

• • Design and implement a metadata-driven framework for managing data attributes across the technology stack.
  • Create a single attribute definition that can generate the required configurations and artifacts currently maintained across multiple components.
  • Establish reusable patterns that simplify the introduction and management of new attributes.
  • Improve consistency, maintainability and operational efficiency across the data platform.

• • Design repeatable processes and frameworks for onboarding new data sources.
  • Reduce data-source onboarding time from weeks or days to hours wherever practical through automation and metadata-driven configuration.
  • Develop scalable ingestion, transformation, enrichment and indexing workflows.
  • Support the initial implementation for one data source and subsequent onboarding of approximately ten additional sources.

• • Redesign the existing Solr architecture to support continued growth beyond the current fixed three-shard layout.
  • Define and optimize SolrCloud sharding, routing, indexing and query strategies.
  • Design solutions for high-volume indexing and low-latency search at scale.
  • Diagnose and resolve search performance, indexing and scalability challenges.
  • Establish best practices for Solr schema design, collections, replicas, shards and query optimization.
  • Ensure the search architecture can scale reliably as data volumes and sources increase.

• • Develop scalable, maintainable and production-ready backend components using Python.
  • Contribute confidently to Java/Spring-based services and APIs.
  • Design robust data-processing pipelines for ingestion, enrichment and serving.
  • Write clean, testable and maintainable code with appropriate documentation and engineering practices.
  • Take ownership of technical solutions from architecture and design through implementation, testing and production deployment.

• • Work closely with a small, experienced engineering team in an autonomous and fast-moving environment.
  • Take ownership of complex technical problems and drive them through to resolution.
  • Participate in architecture and design discussions and contribute to technical decision-making.
  • Collaborate with engineering, product and other stakeholders to translate requirements into scalable technical solutions.
  • Work through short development and feedback cycles to deliver production-ready improvements quickly.

• • Strong production-level experience with Python.
  • Deep hands-on experience with Apache Solr/Lucene, preferably SolrCloud 9 or equivalent large-scale deployments.
  • Strong understanding of Solr architecture, including sharding, routing, indexing, replication, schema design and query optimization.
  • Strong Elasticsearch experience may be considered for candidates who are willing and able to transition to Solr.
  • Working knowledge of Java and the ability to contribute confidently to Spring-based backend services.
  • Strong SQL and data-modeling skills.
  • Experience designing scalable data-ingestion and data-processing pipelines.
  • Experience with data enrichment, indexing and search-serving workflows.
  • Strong understanding of distributed systems and large-scale data platforms.
  • Ability to troubleshoot and optimize high-volume indexing and search workloads.
  • Demonstrated ability to take ownership of complex engineering problems from design through production deployment.

• • Strong Python development experience.
  • Hands-on experience with Solr/Lucene at scale.
  • Strong understanding of SolrCloud, sharding, routing and indexing strategies.
  • Experience with Elasticsearch can be considered with willingness to transition to Solr.
  • Good working knowledge of Java and Spring.
  • Strong SQL and data-modeling skills.
  • Experience building scalable data ingestion and processing workflows.
  • Strong problem-solving and system-design capabilities.
  • Experience working with large-scale data platforms and production environments.

• • Experience working with healthcare data.
  • Knowledge of NEMSIS data and emergency medical records.
  • Experience with Databricks.
  • Front-end development experience.
  • Experience building metadata-driven platforms or configuration frameworks.
  • Experience working with very large-scale datasets and distributed search infrastructure.

• • Strong ownership mindset with the ability to independently drive technical initiatives.
  • Excellent system-design and architectural thinking.
  • Strong analytical and problem-solving skills.
  • Comfortable working with ambiguity and evolving requirements.
  • Ability to balance long-term architecture with short-term delivery requirements.
  • Strong communication and collaboration skills.
  • Comfortable working in a small, senior and highly autonomous engineering team.
  • Passion for building scalable, maintainable and production-ready systems.
  • Ability to learn and adapt quickly to new technologies and domain requirements.