Senior Data Engineer

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    "description": "<p><span style=\"font-weight: bold\">Senior Data Engineer – Data Ingestion &amp; Pipelines</span><br>Location: India (Bangalore) Experience: 4–9 years<br><span style=\"font-weight: bold\">About the Role</span><br>We are looking for a <span style=\"font-weight: bold\">Senior Data Engineer</span> who is deeply comfortable working with data — building ingestion pipelines, writing efficient transformations, exploring different database technologies, and ensuring reliable data movement across the organization.<br>You will primarily work on our <span style=\"font-weight: bold\">Kafka ingestion flow</span>, distributed data systems, and multiple storage layers (SQL, NoSQL, and <span style=\"font-weight: bold\">graph databases</span>). The ideal candidate enjoys working with raw data, optimizing queries, and building stable pipelines using <span style=\"font-weight: bold\">Python and Spark.</span><br>This role is perfect for someone who is data-heavy, curious about the data world.<br><span style=\"font-weight: bold\">Key Responsibilities</span><br><span style=\"font-weight: bold\">Data Engineering (Primary Focus)</span><br>● Build and maintain robust ETL/ELT workflows using <span style=\"font-weight: bold\">Python </span>and <span style=\"font-weight: bold\">Apache Spark</span>.<br>● Design and optimize transformations across SQL, NoSQL, and <span style=\"font-weight: bold\">graph database</span> ecosystems.<br>● Implement data quality checks, schema handling, and consistency across pipelines.<br>● Deal with complex, high-volume datasets and real-world production data.<br><span style=\"font-weight: bold\">Streaming &amp; Ingestion</span><br>● Work on Kafka ingestion pipelines — topics, partitions, consumer logic, schema evolution.<br>● Monitor ingestion performance, throughput, and reliability.<br>● Build connectors/utilities for integrating various sources and sinks.<br><span style=\"font-weight: bold\">Querying &amp; Multi-Database Work</span><br>● Write and optimize complex queries across relational and NoSQL systems.<br>● Exposure to <span style=\"font-weight: bold\">graph databases</span> and <span style=\"font-weight: bold\">graph query languages</span> (e.g., Cypher, Gremlin).<br>● Understand indexing, modeling, and access patterns across different DB types.<br><span style=\"font-weight: bold\">Python &amp; DevOps Awareness</span><br>● Write clean and modular Python code for ETL jobs and data utilities.<br>● Basic understanding of CI/CD, job orchestration, logging, and monitoring.<br>● Ability to debug production ETL issues end-to-end.<br>Required Skills<br>● <span style=\"font-weight: bold\">Strong Python</span> — ETL, utilities, data processing.<br>●<span style=\"font-weight: bold\"> Strong SQL</span> — query optimization and data modeling fundamentals.<br>● <span style=\"font-weight: bold\">Mandatory Spark experience</span> — batch transformations, performance tuning.<br>● Kafka basics — producers, consumers, offsets, schema handling.<br>● Hands-on experience with relational and NoSQL databases.<br>● Exposure to <span style=\"font-weight: bold\">graph databases</span> and <span style=\"font-weight: bold\">graph query languages.</span><br>● Strong debugging and data exploration skills.<br><span style=\"font-weight: bold\">Nice-To-Have</span><br>● Retail or e-commerce domain experience.<br>● Familiarity with Terraform or basic infra automation.<br>● Experience with nested JSON, denormalized structures, and semi-structured data.<br>● Understanding of distributed storage concepts.<br><span style=\"font-weight: bold\">Soft Skills</span><br>● High ownership and end-to-end problem solving.<br>● Enjoys working with complex or messy data.<br>● Curious mindset — comfortable exploring new databases and data flows.<br>● Clear communication and ability to collaborate with backend and product teams.</p>",
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