๐น Key Responsibilities:
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Design & optimize scalable data infrastructure ensuring high availability and reliability.
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Lead & mentor a team of 5+ Data Engineers.
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Define & execute the companyโs data roadmap in collaboration with engineering and analytics teams.
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Ensure data security, governance, and compliance (GDPR, SOC2) across all data platforms.
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Optimize data processing workflows for performance and cost efficiency.
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Drive innovation and implement industry best practices in Big Data, cloud computing, and distributed architectures.
๐น Must-Have Qualifications:
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10+ years of experience in Data Engineering / Software Engineering (Max: 18 years).
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3+ years of leadership experience, managing a team of 5+ Data Engineers.
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8+ years of backend coding experience in Java (Preferred), Python, Node.js, or GoLang.
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Expertise in large-scale distributed architectures using Kafka, Spark, Hive, Hadoop.
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Strong experience with data transformation tools: HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto.
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Hands-on experience in NoSQL databases (Redis, Cassandra, MongoDB, TiDB).
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Expertise in cloud platforms (AWS, GCP, or Azure).
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HLD & LLD experience in designing scalable data solutions.
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Industry Experience: Must have worked in B2B SaaS companies or high-data-traffic analytics products.
๐น Preferred Qualifications:
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Experience in Machine Learning Infrastructure (MLOps).
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Exposure to real-time data processing and data streaming pipelines.
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Strong problem-solving skills with deep knowledge of data structures, algorithms, and scalable architectures.
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Familiarity with DevOps tools: Jenkins, Docker, Kubernetes, Grafana, ELK.
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Prior experience in high-growth SaaS, fintech, or analytics-driven companies
Any Gradute