Senior Manager Dev Engineer A Data and Digital Engineering Services Company

8.0 - 12.0 years

0 Lacs

karnataka

On-site

You will be responsible for designing and implementing highly performant algorithms to process, transform, and analyze large volumes of data. You will apply advanced DSA concepts like Trees, Graphs, Tries, Heaps, and Hashing for data indexing, filtering, and routing. Additionally, you will develop and optimize data pipelines, stream processors, or caching systems, and architect scalable systems for data ingestion, storage, and retrieval (structured/unstructured). Collaboration with cross-functional teams to integrate and deploy performant services will be a key part of your role. You will also perform profiling, tuning, and memory optimization to ensure low-latency operations. Writing clean, modular, testable code and participating in code reviews will be essential responsibilities. To be successful in this role, you should have a strong command over Core DSA concepts such as Binary Search, Heaps, Graphs, Tries, and Trees (AVL, B-Trees, Segment Trees). Hands-on experience with algorithms for sorting, searching, indexing, and caching large datasets is required. Proficiency in one or more of the following languages is necessary: Java, Python. You should also have experience working with large datasets in real-time or batch, along with a solid grasp of time and space complexity and performance tuning. Familiarity with memory management, garbage collection, and data locality is important. Deep technical knowledge and hands-on experience in architecture design, development, deployment, and production operation are crucial. Familiarity with agile software development and modern development tools and frameworks is expected, along with strong engineering principles, including automation, quality, and best practices with a high bar. Extensive experience in the complete software development life cycle E2E, including production monitoring, will be beneficial. It would be good to have a broad understanding of Data Lakehouse formats like Apache Hudi, Apache Iceberg, or Delta Lake. Demonstrable experience in Spark programming and experience with Spark on DBT with AWS Glue or Apache Polaris is a plus. A broad understanding of cloud architecture tools and services, such as S3, EMR, Kubernetes, and Lambda functions, is desirable. Experience in AWS and Azure is also highly desirable. Rich experience and deep expertise in Big Data and large-scale data platforms, especially in Data Lake, would be advantageous.,

Posted 1 week ago

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