Data Engineering Senior Analyst [T500-12862]
Job details
Role Title: Software Engineer (Advisor) Position Summary: Cigna, a leading Health Services company, is looking for an exceptional engineer in our Data & Analytics Engineering organization. The Full Stack Engineer is responsible for the delivery of a business need starting from understanding the requirements to deploying the software into production. This role requires you to be fluent in some of the critical technologies with proficiency in others and have a hunger to learn on the job and add value to the business. Critical attributes of being a Full Stack Engineer, among others, is ownership, eagerness to learn & an open mindset. In addition to Delivery, the Full Stack Engineer should have an automation first and continuous improvement mindset. Person should drive the adoption of CI/CD tools and support the improvement of the tools sets/processes. Job Description & Responsibilities:
- Design and architect the solution independently
- Take ownership and accountability
- Write referenceable & modular code
- Be fluent in particular areas and have proficiency in many areas Have a passion to learn
- Have a quality mindset, not just code quality but also to ensure ongoing data quality by monitoring data to identify problems before they have business impact
- Take risks and champion new ideas
- 3+ years of experience required in listed skills in Data Engineering role
- 3+ years of Python scripting experience
- 3+ years of Data Management & SQL expertise – Teradata & Snowflake experience strongly preferred
- 3+ years being part of Agile teams – Scrum
- Experience with version management tools – Git preferred
- Experience with BDD and TDD development methodologies
- Experience working in an agile CI/CD environments; Jenkins experience preferred
- Knowledge and/or experience with Health care information domains preferred
- Bachelor’s degree (or equivalent) required
- Expertise with big data technologies - Hadoop, HiveQL, Spark (Scala/Python) Expertise on Cloud technologies – AWS (S3, Glue, Terraform, Lambda, Aurora, Redshift, EMR)
- Experience working on Analytical Models and their deployment / production enable? ment via data & analytics pipelines
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