A Cloud Software & Data Engineer is responsible for developing data engineering applications using third-party and in-house frameworks, leveraging a broad set of development skills that cover data engineering, data accessibility skillsets. The Cloud Software & Data Engineer is responsible for the complete software lifecycle – analysis, design, development, testing, implementation and support, as well as troubleshooting issues, deployment/upgrade of services and associated data, performance tuning and other maintenance work. This specific type of cloud developer will focus on additional items: data engineering (large scale data transformation and manipulation, ETL, etc.), as well as infrastructure fine-tuning for optimization purposes. The position reports to the software project manager.

Responsibilities

• Work with subject matter experts to clarify requirements and use cases.
• Turn requirements and user stories into functionality via implementation efforts which include: design, build & maintain efficient, reusable, reliable code for high quality software and services, documentation and traceability.
• Develop server-side services to be elastically scalable and secure by design to support high volume & high velocity data processing. Services should be backward and forward compatible to ease deployment.
• Ensure the solution is deployable, operable, and secure.
• Write and maintain provisioning, deployment, CI/CD and maintenance scripts for services they developed.
• Write Unit Tests, Automation testing, Data Simulations.
• Support, maintain, troubleshoot and fine-tune working cloud environments and the software run within.
• Builds prototypes, products and systems that meets the project quality standards and requirements.
• Be an individual contributor which includes technical leadership and documentation to developers and stakeholders.
• Provide timely corrective actions on all assigned defects and issues.
• Contributes to development plan by providing task estimates.
• Fulfil organizational responsibilities (sharing knowledge & experience with other teams/ groups)
• Conduct technical training(s)/session(s), write whitepapers/case studies/blogs etc.

• Bachelor’s degree or higher in Computer Science or related with minimum 5 years working experience.
• 5 years of software development experience in Big Data technologies (Spark Database & Data Lakes).
• SQL, No-SQL, JSON, CSV, Parquet data type experience.
• Advanced knowledge of large-scale parallel computing engines (Spark) – provisioning, deployment, development of computing pipelines, operation and support with performance tuning (3y ).
• Good experience in building/tuning Spark pipelines in Python.
• Good Programming experience with Python.
• Design, build and maintain data processing pipelines in Apache NiFi, Spark Jobs.
• Extensive knowledge of data structures, patterns and algorithms (5y ).
• Expertise with several back-end development languages and their associated frameworks like Python (3y ).
• In-depth knowledge of application, cloud networking and security as well as related development best-practices and patterns (3y ).
• Advanced knowledge of containerization and virtualization (Kubernetes), as well as scaling clusters & debugging issues on high volume/velocity data jobs and best practices (3y ).
• Good experience in Spark, Databricks on Kubernetes.
• Cloud platform knowledge – Azure public cloud expertise (3y ).
• Advanced knowledge of DevOps, CI/CD and cloud deployment practices (5y ).
• Advanced skills in setting up and operating databases (relational and non-relational) (3y )
• Experienced in application profiling, bottleneck analysis and performance tuning.
• Effective communication and cross functional skills.
• Problem solving skills, Team player, adaptable & quick worker.
• Have worked in highly Agile projects in the past.