Job
Description
Position Summary: S.E Analyst demonstrates expertise in data engineering technologies with the focus on engineering, innovation, strategic influence and product mindset. This individual will act as a key contributor of the team to design, build, test and deliver large-scale software applications, systems, platforms, services or technologies in the data engineering space. This individual will have the opportunity to work directly with partner IT and business teams, owning and driving major deliverables across all aspects of software delivery. The candidate will play a key role in automating the processes on Databricks and AWS. They collaborate with business and technology partners in gathering requirements, develop and implement. The individual must have strong analytical and technical skills coupled with the ability to positively influence the delivery of data engineering products. The applicant will be working in a team that demands innovation, cloud-first, self-service-first, and automation-first mindset coupled with technical excellence. The applicant will be working with internal and external stakeholders and customers for building solutions as part of Enterprise Data Engineering and will need to demonstrate very strong technical and communication skills. Job Description & Responsibilities: The candidate will be responsible to deliver business needs end to end from requirements to development into production. Through hands-on engineering approach in Databricks environment, this individual will deliver data engineering toolchains, platform capabilities and reusable patterns. The applicant will be responsible to follow software engineering best practices with an automation first approach and continuous learning and improvement mindset. The applicant will ensure adherence to enterprise architecture direction and architectural standards. The applicant should be able to collaborate in a high-performing team environment, and an ability to influence and be influenced by others. Experience Required: More than 6 months to 1.5 years of experience in software engineering, building data engineering pipelines, middleware and API development and automation Experience Desired: Expertise in Agile software development principles and patterns Expertise in building streaming, batch and event-driven architectures and data pipelines Primary Skills: Experience in messaging systems such as Apache ActiveMQ, WebSphere MQ, Apache Artemis, Kafka, AWS SNS Proficient in self-testing of applications, unit testing and use of mock frameworks, test-driven development (TDD) Knowledge on Behavioral Driven Development (BDD) approach (Spark or Scala) with Aws, Python Additional Skills: Ability to perform detailed analysis of business problems and technical environments Strong oral and written communication skills Ability to think strategically, implement iteratively and estimate financial impact of design/architecture alternatives Continuous focus on an on-going learning and development AWS Certifications - nice to have Devops, CI/CD, Databricks
