Data Platform Engineer (SDE 2 / SDE 3)

Job Title : Data Platform Engineer (SDE 2 / SDE 3) Experience : 3 to 8 Years (SDE2 : 3 to 5 Years | SDE3 : 5.5 to 8 Years) Location : Remote (Contract) Pune (Post Conversion) Employment Type : Contract-to-Hire (3 Months) Mandatory Skills : Java / Python / Go, SQL, Data Engineering, ETL / ELT, Apache Airflow, Apache Spark / Flink, Kafka, AWS/GCP/Azure, Distributed Systems, API Development, Docker, Kubernetes, CI/CD, System Design Role Overview : We are looking for a Data Platform Engineer with strong backend engineering expertise to build scalable, high-performance data platforms and distributed systems. The ideal candidate should have hands-on experience in developing production-grade backend applications along with designing and maintaining modern data pipelines. Key Responsibilities : Build and maintain scalable ETL/ELT and data processing pipelines.Develop backend services and APIs using Java (preferred), Python, or Go.Design batch and real-time data pipelines using Spark, Flink, Kafka, and Airflow.Optimize SQL queries, data models, and distributed data systems.Work with cloud platforms (AWS, GCP, or Azure) and container technologies (Docker, Kubernetes).Implement CI/CD, monitoring, logging, and performance optimization.Collaborate with product and engineering teams on scalable system design and architecture. Required Qualifications : SDE 2 : 3 to 5 years of Backend + Data Engineering experience.SDE 3 : 5.5 to 8 years of Backend + Data Engineering experience.Strong coding skills in Java (preferred), Python, or Go.Excellent SQL and data modeling knowledge.Hands-on experience with Airflow, Apache Spark / Apache Flink, or similar technologies.Experience building scalable backend services and APIs.Good understanding of distributed systems, system design. and scalable architecture.Experience with cloud platforms (AWS, Azure, or GCP).Hands-on experience with Docker and Kubernetes.Strong understanding of CI/CD pipelines.Excellent problem-solving and debugging skills. Good to Have : Experience with Snowflake, BigQuery, or Redshift.Understanding of Kafka, Kinesis, or Pub/SubPerformance optimization of large-scale distributed systemsFinTech or high-scale distributed systems experience.Knowledge of data governance, security, and compliance. Preferred Candidate Profile : Strong Backend + Data Engineering experienceExperience building scalable production systemsStrong ownership mindsetGood system design knowledgeExperience processing millions of events using Kafka/SparkBuilt APIs supporting data infrastructureProduction engineering experience Interview Process : Take-home Coding Assignment (48 Hours)Leadership & Strategy Round (1 Hour)Technical Depth Data Engineering & Performance (1 Hour)Culture & Values Fit (30 Minutes) .