JD

Job Objective

As a Lead Backend Engineer, you will be responsible for designing, developing, and maintaining scalable data pipelines and search infrastructure. You will play a key role in architecting high-performance search solutions using Elasticsearch while working closely with cross-functional teams to ensure efficient data processing and retrieval across the technology stack. You will also mentor engineers, drive best practices, and ensure high standards in system reliability, performance, and data quality.

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Search Infrastructure: Design, develop, and maintain Elasticsearch clusters for large-scale search and analytics use cases.

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Data Pipeline Development: Build and optimize data pipelines using Apache Spark and Scala for batch and real-time data processing.

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Cluster Management: Manage configuration, tuning, and scaling of distributed clusters to ensure optimal performance and reliability.

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Workflow Orchestration: Design and implement data workflows using Apache Airflow for scheduling, monitoring, and managing complex ETL pipelines

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Backend Development: Develop and maintain backend services using Java to support search and data processing functionalities.

? Architecture &

- Scalability: Contribute to backend architecture decisions to ensure high scalability, reliability, and performance of data systems.

? Troubleshooting &
- Debugging: Diagnose complex issues in search infrastructure and data pipelines and drive resolution to maintain system stability.

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Collaboration: Work closely with data scientists, backend developers, DevOps teams, product managers,



and other stakeholders to deliver data solutions.

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Technical Leadership: Provide technical guidance and mentorship to junior engineers while ensuring adherence to engineering best practices.

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Documentation: Maintain comprehensive documentation for data pipelines, search configurations, and system architecture.

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Continuous Improvement: Stay updated with emerging technologies and recommend improvements to enhance data processing and search capabilities.

? Testing &

- Validation: Drive test planning and validation processes to ensure reliability and integrity of search and data systems.

Required Skills

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Experience: 5?6 years of hands-on experience in backend development with solid expertise in Elasticsearch, Java, Apache Spark, and Scala.

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Cluster Configuration: Strong experience in managing and configuring distributed clusters, including Elasticsearch cluster management, tuning, and optimization.

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Data Engineering: Proficiency in data engineering practices including workflow orchestration using Apache Airflow.

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System Design: Experience in designing scalable and high-performance search and data systems.

? Problem-Solving Skills: Strong analytical and troubleshooting abilities with a solution-oriented mindset.

? Ownership &

- Accountability: High sense of responsibility and ownership for project deliverables and system stability.

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Communication: Excellent verbal and written communication skills.

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Team Leadership: Ability to mentor team members and collaborate effectively within cross functional teams.

📌 Lead Engineer (Noida)
🏢 Info Edge
📍 Noida