Sr. Manager Data Engineering

What you do

We are seeking a seasoned Sr Manager of Data Engineering to drive the development and implementation of our data strategy for Manufacturing and Clinical Supply Chain. The ideal candidate possesses a strong blend of technical expertise and data-driven problem-solving skills. As a Sr Manager Data Engineering, you will play a crucial role in leading, designing, building, and optimizing our data pipelines and platforms while mentoring junior engineers.

Roles & Responsibilities:

• Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions.
• Take ownership of data pipeline projects from inception to deployment, managing scope, timelines, and risks.
• Ensure data quality and integrity through rigorous testing and monitoring.
• Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions.
• Work closely with data analysts, data scientists, and business stakeholders to understand data requirements.
• Identify and resolve complex data-related challenges.
• Adhere to data engineering best practices and standards.
• Experience developing in an Agile development environment, and comfortable with Agile terminology and ceremonies.
• Familiarity with code versioning using GIT, Jenkins and code migration tools.
• Exposure to Jira.
• Identifying and implementing opportunities for automation and CI/CD.
• Stay up to date with the latest data technologies and trends.

What we expect of you

• We are all different, yet we all use our unique contributions to serve patients.

Basic Qualifications:

• Doctorate degree / Master's degree / Bachelor's degree and 12 to 17 years of experience in Computer Science, IT or related field

Functional Skills:

Must-Have Skills:

• 5+ years of managerial experience directly managing people and/or leadership experience leading teams, projects, programs or directing the allocation of resources
• Demonstrated hands-on experience with cloud platforms (AWS, Azure, GCP) and the ability to architect cost-effective and scalable data solutions.
• Proficiency in Python, PySpark, SQL. Hands on experience with big data ETL performance tuning.
• Strong development knowledge in Databricks.
• Strong analytical and problem-solving skills to address complex data challenges.

Preferred Qualifications

Good-to-Have Skills:

• Experienced with data modeling and performance tuning
• Experienced working with Apache Spark, Apache Airflow
• Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops
• Experience in SQL/NOSQL database, vector database for large language models
• Experience with prompt engineering, model fine tuning
• Experience with DevOps/MLOps CICD build and deployment pipeline

Professional Certifications :

• AWS Certified Data Engineer (preferred)
• Databricks Certification (preferred)
• Any SAFe Agile certification (preferred)

Soft Skills:

• Initiative to explore alternate technology and approaches to solving problems.
• Skilled in breaking down problems, documenting problem statements, and estimating efforts.
• Effective communication and interpersonal skills to collaborate with cross-functional teams.
• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication skills
• Ability to work effectively with global, virtual teams
• High degree of initiative and self-motivation.
• Ability to manage multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals
• Strong presentation and public speaking skills.