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Software Development Engineer

  • Source: Naukri
  • Mastek
  • $20,970.96 to $28,835.06 /yr
  • On-site
  • Bengaluru
  • Full-Time
  • Mid level

Job Description

Role & responsibilities

Key Responsibilities

  • Design, develop, and maintain end-to-end data pipelines and ETL/ELT processes using Databricks and other data engineering tools to support analytics and BI use cases.
  • Build and deploy cloud-native data and analytics solutions on AWS, leveraging services such as EKS, S3, and other relevant components for scalable and resilient architectures.
  • Develop backend services and APIs using Python and Flask to enable data access, automation workflows, and integration with downstream applications and dashboards.
  • Implement containerization and orchestration using Docker and Kubernetes (EKS preferred) to ensure reliable, portable, and scalable deployment of data and analytics workloads.
  • Set up and maintain CI/CD pipelines using Jenkins/Jenkins Core to automate build, test, and deployment processes for data engineering and analytics solutions.
  • Collaborate with data scientists, analysts, and BI developers to enable AI, machine learning, and advanced analytics use cases through well-structured, high-quality data.
  • Optimize data models, queries, and pipelines for performance, cost efficiency, and reliability across large-scale datasets and complex analytics workloads.
  • Implement data quality checks, monitoring, logging, and alerting to ensure data reliability, integrity, and timely availability for business stakeholders.
  • Contribute to data automation initiatives by identifying opportunities to streamline manual processes and implementing robust automation solutions.
  • Ensure adherence to best practices in cloud security, data governance, and compliance for all data engineering and analytics solutions.
  • Support troubleshooting, root cause analysis, and performance tuning for data pipelines, cloud infrastructure, and analytics platforms.
  • Mentor junior team members and contribute to knowledge sharing, coding standards, and best practices within the data engineering and analytics team.

Skills

  • azure-databricks
  • databricks
  • amazon-web-services
  • amazon-eks
  • amazon-s3
  • Python
  • Flask
  • Docker
  • Kubernetes
  • Jenkins
  • streamline

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