Job Description :

We are looking for a passionate and skilled Software Engineer with a strong foundation in Data Structures and Algorithms (DSA) and experience in building systems that handle large-scale data efficiently. Youll play a key role in designing, developing, and optimizing backend systems, real-time pipelines, or storage engines that scale to billions of records.

Role & Responsibilities :

- Design and implement highly performant algorithms to process, transform, and analyze large volumes of data

- Apply advanced DSA concepts like Trees, Graphs, Tries, Heaps, and Hashing for data indexing, filtering, and routing

- Develop and optimize data pipelines, stream processors, or caching systems

- Architect scalable systems for data ingestion, storage, and retrieval (structured/unstructured)

- Collaborate with cross-functional teams to integrate and deploy performant services

- Perform profiling, tuning, and memory optimization to ensure low-latency operations

- Write clean, modular, testable code and participate in code reviews

Must-Have Skills :

- Strong command over Core DSA concepts: Binary Search, Heaps, Graphs, Tries, Trees (AVL, B-Trees, Segment Trees)

- Hands-on experience with algorithms for sorting, searching, indexing, and caching large dataset

- Proficiency in one or more of the following languages : Java, Python

- Experience working with large datasets in real-time or batch

- Solid grasp of time and space complexity and performance tuning

- Familiarity with memory management, garbage collection, and data locality

- Deep technical knowledge; hands-on in architecture design, development, deployment, and production operation; familiar with agile software development and modern development tools and frameworks; holds strong engineering principles, including automation, quality, and best practices with a high bar.

- Extensive experience in complete software development life cycle E2E, including production monitoring.

Good to have :

- Broad understanding of Data Lakehouse formats like Apache Hudi, Apache Iceberg or Delta Lake.

- Demonstrable experience in Spark programming

- 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.