Senior Data Engineer
Paytm · Noida · 3+ yrs experience · Posted 2026-04-14
Tech stack: AWS, Cassandra, Docker, GCP, Java, Kafka, Kubernetes, MongoDB, PostgreSQL, Python, SQL, Scala, Spring Boot, Microservices, Airflow, Apache Spark, Apache NiFi, Apache Flink
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About the role
About the Role:
We are looking for a highly skilled Data Engineer to design, build, and optimize scalable data systems that power our products and insights. You will work closely with cross-functional teams to develop robust data infrastructure, ensure data quality, and enable data-driven decision-making across the organization.
Key Responsibilities:
● Design, develop, and maintain scalable data pipelines for ingestion, processing, and storage
● Build and manage ETL workflows using tools such as Apache Spark, Apache NiFi, or similar technologies
● Integrate data from multiple sources into centralized data warehouses or data lakes
● Collaborate with data scientists, analysts, and engineers to translate business needs into technical solutions
● Ensure data quality, integrity, and reliability through validation and monitoring processes
● Optimize data pipelines for performance, scalability, and efficiency
● Monitor, troubleshoot, and resolve production issues with minimal downtime
● Implement best practices in data governance, security, and compliances
● Contribute to continuous improvement, automation, and system reliability
● Document workflows, systems, and technical specification
Responsibilities:
- We are looking for a highly skilled Data Engineer to design, build, and optimize scalable data systems that power our products and insights.
- You will work closely with cross-functional teams to develop robust data infrastructure, ensure data quality, and enable data-driven decision-making across the organization.
- Design, develop, and maintain scalable data pipelines for ingestion, processing, and storage
- Build and manage ETL workflows using tools such as Apache Spark, Apache NiFi, or similar technologies
- Integrate data from multiple sources into centralized data warehouses or data lakes
- Collaborate with data scientists, analysts, and engineers to translate business needs into technical solutions
- Ensure data quality, integrity, and reliability through validation and monitoring processes
- Optimize data pipelines for performance, scalability, and efficiency
- Monitor, troubleshoot, and resolve production issues with minimal downtime
- Implement best practices in data governance, security, and compliances
- Contribute to continuous improvement, automation, and system reliability
- Document workflows, systems, and technical specification
- Stay updated with emerging trends and technologies in data engineering
- Build systems to collect and transform complex datasets for production use
- Develop and maintain backend services and data infrastructure
- Implement scalable data schemas and improve data management practices
- Provide insights into product performance and customer behavior
- Act as a subject matter expert in data infrastructure, privacy, and security
- Collaborate with stakeholders to understand and deliver on requirements
- Participate in on-call rotations to support live systems
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
- 3+ years of experience in data engineering or backend engineering
- Strong understanding of data structures and algorithms
- Proficiency in Java, Python, or Scala
- Strong SQL skills with the ability to write complex queries
- Experience with workflow orchestration tools such as Airflow
- Hands-on experience with big data technologies like Apache Spark, Kafka, or Flink
- Experience with databases such as Cassandra, MongoDB, Oracle, or PostgreSQL
- Familiarity with cloud platforms (AWS or GCP)
- Experience with containerization tools like Docker and Kubernetes
- Experience building scalable microservices using REST, Spring Boot, or gRPC
- Strong problem-solving, communication, and collaboration skills
- Experience with large-scale distributed systems
- Knowledge of data security and compliance standards
- Experience in building and scaling data platforms
- Passion for experimentation, rapid prototyping, and innovation
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
- 3+ years of experience in data engineering or backend engineering
- Strong understanding of data structures and algorithms
- Proficiency in Java, Python, or Scala
- Strong SQL skills with the ability to write complex queries
- Experience with workflow orchestration tools such as Airflow
- Hands-on experience with big data technologies like Apache Spark, Kafka, or Flink
- Experience with databases such as Cassandra, MongoDB, Oracle, or PostgreSQL
- Familiarity with cloud platforms (AWS or GCP)
- Experience with containerization tools like Docker and Kubernetes
- Experience building scalable microservices using REST, Spring Boot, or gRPC
- Strong problem-solving, communication, and collaboration skills
- Experience with large-scale distributed systems
- Knowledge of data security and compliance standards
- Experience in building and scaling data platforms
- Passion for experimentation, rapid prototyping, and innovation
Responsibilities
- We are looking for a highly skilled Data Engineer to design, build, and optimize scalable data systems that power our products and insights.
- You will work closely with cross-functional teams to develop robust data infrastructure
- ensure data quality, and enable data-driven decision-making across the organization.
- Design, develop, and maintain scalable data pipelines for ingestion, processing, and storage
- Build and manage ETL workflows using tools such as Apache Spark, Apache NiFi, or similar technologies
- Integrate data from multiple sources into centralized data warehouses or data lakes
- Collaborate with data scientists, analysts, and engineers to translate business needs into technical solutions
- Ensure data quality, integrity, and reliability through validation and monitoring processes
- Optimize data pipelines for performance, scalability, and efficiency
- Monitor, troubleshoot, and resolve production issues with minimal downtime
- Implement best practices in data governance, security, and compliances
- Contribute to continuous improvement, automation, and system reliability
- Document workflows, systems, and technical specification
- Stay updated with emerging trends and technologies in data engineering
- Build systems to collect and transform complex datasets for production use
- Develop and maintain backend services and data infrastructure
- Implement scalable data schemas and improve data management practices
- Provide insights into product performance and customer behavior
- Act as a subject matter expert in data infrastructure, privacy, and security
- Collaborate with stakeholders to understand and deliver on requirements
- Participate in on-call rotations to support live systems