Data Engineer - ML Platforms

at  CVS Health

Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver.
Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.

POSITION SUMMARY

• Analyzes complex Data structure from various data sources and design large scale data engineering pipeline.
• Implement data ingestion pipeline using APIs, third party tools, or create custom codes to ingest high volume data into Cloud environment.
• Collaborate with cross functional team to understand business requirements and translate them into technical specifications.
• Develops large scale data structures and pipelines to organize, collect and standardize data that helps generate insights and addresses reporting needs.
• Implements data quality checks and validation processes to ensure the accuracy, completeness, and consistency of the data.
• Documents data engineering processes, workflows, and systems for reference and knowledge-sharing purposes.
• Uses strong programming skills in SQL, pyspark, Python, Java or any of the major languages to build robust data pipelines and dynamic systems
• Be a team player and work with team members for Business solution and implementation.
• Ideal Candidate needs to continuously learn and adopt business subject matter expertise and emerging algorithms and techniques.
• Analyze and optimize pipelines to reduce cost while maintaining accuracy.
• Create workflow efficiencies, raise the bar for coding, work with distributed computing and model training
• Ideal candidate will design and implement advanced ML algorithms and models while ensuring smooth operation and maintenance of existing applications.

REQUIRED QUALIFICATIONS

• 3+ years of building cloud native analytical products in GCP, Azure or AWS
• Sound knowledge in any of cloud Technology is must preferably Google cloud Platform (GCP)
• 3+ years hands-on experience working in scalable distributed computation frameworks like Spark.
• 3+ years of Data & Analytics related software development experience in designing & developing ML pipelines, metadata frameworks, reusable components and/or platforms.
• 3+ years hands-on experience working in Dev/ML Ops model, familiarity with industry deployment best practices using CI/CD
• Knowledge in programing languages such as SQL , Python, Pyspark or Java/Scala
• Experience with bash shell scripts, UNIX utilities & UNIX Commands
• Strong problem-solving skills and critical thinking ability
• Strong collaboration and communication skills within and across teams

PREFERRED QUALIFICATIONS

• Experience with Healthcare domain is highly desirable.
• Hands-on ML-centric programming experience with either Python(preferred), Java or R
• Hands-on experience in developing AI solutions leveraging Python libraries such as PyTorch, Tensorflow, Scikit-Learn, XGBoost
• Expertise working with ML platforms & toolsets such as Vertex AI is preferred.
• Exposure in implementing Unsupervised Model, Gen AI and/or NLP based solutions using LLMs.
• Strong interpersonal and communication skills, including the ability to explain and discuss machine learning concepts with cross functional teams.
• Exposure to Agile Methodology
• GCP Certifications: Associate Cloud Engineer/Professional Data Engineer.

EDUCATION

• Bachelor’s degree or equivalent work experience in Mathematics, Statistics, Computer Science, Business Analytics, Data Science, Engineering, or related discipline
• Master’s degree Preferred in Computer Science/ML

Please refer the Job description for details