Evernorth Customer Data Platform Engineering team is looking for a Software Engineering Senior Advisor highly skilled in Data Engineering with hands-on experience working with Snowflake. The ideal candidate will have a strong background in Big Data technologies, including Apache Spark (Python or Scala), and expertise in orchestration and integration tools such as Apache Airflow or NiFi, or DBT. Experience with cloud services, preferably AWS, is essential for designing and implementing scalable data pipelines in the cloud. This role offers the opportunity to work on cutting-edge data engineering projects and collaborate with cross-regional teams to deliver innovative solutions.
In this role, you will provide hands-on software engineering and system architecture leadership for our CDP teams. You will be working on several of the largest Technology initiatives for Evernorth℠ targeted at revolutionizing Health Services and Healthcare Delivery system in the United States. The focus of the work is to continue to enhance our market winning capabilities in the pharmacy and PBM space.
The Evernorth℠Technology strategy is fully aligned with our business strategy, resulting in an opportunity for you to influence in various directions – this includes technology\business direction.
Responsibilities
Snowflake Expertise: Design, develop, and optimize data pipelines using Snowflake, including building and maintaining multi-layered data models. Optimize queries, ensure performance, and manage the cost efficiency of Snowflake environments.
Cloud Experience: Extensive experience working with AWS or other cloud platforms (such as Azure or Google Cloud) to design, deploy, and manage scalable data solutions. Proficient in utilizing cloud-native services for data storage, processing, and orchestration (e.g., S3, EMR, EC2, Redshift, Athena, Lambda, Glue). Familiar with setting up and managing cloud environments for optimal performance and cost-efficiency.
Big Data Engineering: Lead the design and development of Big Data solutions using Apache Spark (Python/Scala), enabling the processing of petabytes of data in both real-time and batch modes. Work with both structured and unstructured data to build efficient data architectures.
Data Orchestration & Integration: Develop and manage end-to-end ETL/ELT pipelines using Apache Airflow, Apache NiFi, DBT, or other equivalent orchestration tools. Automate data workflows, schedule tasks, and ensure the reliability of data pipelines.
Data Modeling: Design and implement scalable and efficient data models for data storage and retrieval, ensuring data accessibility and optimization. Work on building and managing multi-layered data models that facilitate easy analysis and reporting.
Real-Time Data Streaming: Work with Kafka or other streaming technologies to enable real-time data ingestion and processing. Build and optimize stream processing solutions to integrate event-driven data sources into the pipeline.
Collaboration & Leadership: 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.
SQL & Database Management: Write complex SQL queries to transform and process data across relational and columnar databases. Design and maintain scalable database architectures for both operational and analytical workloads.
Innovation & Optimization: Continuously seek ways to improve the performance, scalability, and reliability of the data platform. Drive innovation by researching and applying the latest tools and technologies in the data engineering space.
Qualifications
Required Skills:
5-8 years of experience in Data Engineering, with a proven track record of designing and building data pipelines and architectures at scale.
At least 4 years of hands-on experience with Snowflake, including data modeling and query optimization, designing and implementing multi-layered data architectures
Experience with cloud services, preferably AWS (e.g., S3, EMR, EC2, Redshift, Athena, Lambda, Glue), for designing, deploying, and managing scalable data solutions.
Strong experience in Big Data technologies like Spark (Python/Scala) for large-scale data processing.
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), with advanced SQL query writing skills.
Hands-on experience with Kafka or equivalent streaming data systems to process real-time data.
Strong problem-solving skills and the ability to troubleshoot complex issues in distributed systems.
Proven ability to collaborate with offshore teams and coordinate across time zones to deliver successful projects.
Experience with version control systems like Bitbucket or GitHub, and project management tools such as Jira, with familiarity in working within an Agile/Sprint model.
Good to have experience with Jenkins for continuous integration and deployment (CI/CD) pipelines and Terraform for infrastructure as code (IaC) automation.
Required Experience & Education:
5-8 Years of Experience
College degree (Bachelor) in related technical/business areas or equivalent work experience.
Desired Experience:
Exposure to AWS
Healthcare experience
Coaching of team members
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