Evernorth Health Services India
Health Services
SoftwareEngineeringLeadAnalyst
“Software Engineering Lead Analyst at Evernorth Health Services India. Skills: Snowflake, AWS, Apache Spark, Apache Airflow, DBT, Kafka. Design, develop, and optimize data pipelines using Snowflake. Build and maintain multi-layered data models”
What You'll Achieve.
Deliver innovative solutions; Enhance market winning capabilities in the pharmacy and PBM space; Deliver high-quality data engineering solutions on time and within budget
Industry & Context.
problem-solving skills; ability to troubleshoot complex issues in distributed systems
Work Hours: 11.30 AM IST to 8.30PM IST
What They're Looking For.
Must Have
5-8 years of experience in Data Engineering, At least 4 years of hands-on experience with Snowflake, Experience with cloud services, preferably AWS (e.g., S3, EMR, EC2, Redshift, Athena, Lambda, Glue), experience in Big Data technologies like Spark (Python/Scala), Proficiency in Data Orchestration and Integration tools, such as Apache Airflow, Apache NiFi, DBT, or equivalent, Expertise in working with relational (e.g., SQL Server, PostgreSQL) and columnar databases (e.g., AWS Redshift, Snowflake), Hands-on experience with Kafka or equivalent streaming data systems, problem-solving skills, Proven ability to collaborate with offshore teams and coordinate across time zones, Experience with version control systems like Bitbucket or GitHub, Experience with project management tools such as Jira, familiarity in working within an Agile/Sprint model, College degree (Bachelor) in related technical business areas or equivalent work experience
Nice to Have
Exposure to AWS, Healthcare experience, Coaching of team members, Experience with Jenkins for continuous integration and deployment (CI/CD) pipelines, Experience with Terraform for infrastructure as code (IaC) automation
What You'll Do.
and optimize data pipelines using Snowflake
Build and maintain multi-layered data models
and manage cost efficiency of Snowflake environments
and manage scalable data solutions using cloud platforms (AWS
Utilize cloud-native services for data storage
Set up and manage cloud environments for optimal performance and cost-efficiency
Lead the design and development of Big Data solutions using Apache Spark (Python/Scala)
Process petabytes of data in both real-time and batch modes
Work with both structured and unstructured data to build efficient data architectures
Develop and manage end-to-end ETL/ELT pipelines using Apache Airflow
or other equivalent orchestration tools
Automate data workflows
and ensure the reliability of data pipelines
Design and implement scalable and efficient data models for data storage and retrieval
Build and manage multi-layered data models that facilitate easy analysis and reporting
Work with Kafka or other streaming technologies to enable real-time data ingestion and processing
Build and optimize stream processing solutions
Write complex SQL queries to transform and process data
Design and maintain scalable database architectures
Continuously seek ways to improve the performance
and reliability of the data platform
Drive innovation by researching and applying the latest tools and technologies in the data engineering space
How You'll Work.
Team & Collaboration
Work with cross-functional teams, including product, engineering, to develop and implement data solutions; Manage and coordinate with offshore development teams to deliver high-quality data engineering solutions on time and within budget; Collaborate with offshore teams and coordinate across time zones
Process & Methodology
Experience with project management tools such as Jira, Familiarity in working within an Agile/Sprint model
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