About the Role

We are looking for a Software Development Engineer (SDE) with strong experience in large-scale data handling and backend engineering to join our growing engineering team in Kolkata. The role focuses on building scalable data pipelines, optimizing high-volume data systems, and developing reliable backend services using Python, MySQL, and Databricks.

You will work closely with data engineers, product teams, and platform teams to design and maintain systems capable of processing and analyzing large datasets efficiently.

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Key Responsibilities

• Design, develop, and maintain scalable backend systems and data pipelines.

• Handle large-scale structured and unstructured datasets with high performance and reliability.

• Build data ingestion, transformation, and processing workflows using Python and Databricks.

• Optimize database queries, schemas, and indexing strategies in MySQL for performance at scale.

• Develop APIs and backend services to support internal and external applications.

• Collaborate with cross-functional teams to understand data requirements and system dependencies.

• Monitor, troubleshoot, and improve existing data infrastructure and processing jobs.

• Ensure code quality through testing, code reviews, and engineering best practices.

• Participate in architecture discussions and contribute to technical decisionmaking.Required Skills & Qualifications

• Strong programming experience in Python.

• Solid understanding of large-scale data processing and distributed systems.

• Hands-on experience with MySQL, including query optimization and database design.

• Experience working with Databricks, Apache Spark, or similar big data platforms.

• Good understanding of ETL workflows and data engineering concepts.

• Familiarity with REST APIs and backend service development.

• Experience with cloud platforms such as AWS, Azure, or GCP is a plus.

• Strong problem-solving and analytical skills.

• Good communication and collaboration abilities.

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Preferred Qualifications

• Experience handling millions of records or real-time data pipelines.

• Knowledge of data warehousing and analytics platforms.

• Exposure to containerization and orchestration tools such as Docker or Kubernetes.

• Understanding of CI/CD pipelines and DevOps practices