Lead Data Security Engineer

Centene; United States; On-site; USD 100,000 - 187,000; Full time

Job summary

Centene is seeking a Data Engineer/Scientist to enhance security infrastructure through advanced data engineering and analysis. This role includes creating efficient data pipelines, mentoring junior team members, and collaborating with cross-functional teams. The ideal candidate will have a robust technical background in data management, machine learning, and visualization, alongside a strong emphasis on data governance.

Benefits

Health insurance

401K and stock purchase plans

Tuition reimbursement

Paid time off plus holidays

Flexible work schedules

Qualifications

• 5-7 years related experience required.
• Proficiency in data pipeline design and automation.
• Databricks certification preferred.

Responsibilities

• Develop data engineering strategies and pipelines for security data lake.
• Mentor junior developers and conduct code reviews.
• Analyze datasets using statistical techniques to derive insights.

Skills

Data quality and governance

Machine learning model development

Data visualization

Strong problem-solving skills

Excellent communication

Education

Bachelor's degree in quantitative or business field

Tools

Databricks

SQL

Python

Tableau

Power BI

AWS

Azure

GCP

Hadoop

Spark

Job description

You could be the one who changes everything for our 28 million members by using technology to improve health outcomes around the world. As a diversified, national organization, Centene's technology professionals have access to competitive benefits including a fresh perspective on workplace flexibility.

Position Purpose:

This role will support the Threat Infrastructure Security tools in the Centene environment.This role's focus will be Data engineering/science for a Security Data Lake and automation projects. This role includes: develop strategy, execute design and implement efficient data pipelines to ensure a smooth flow of information into the Security Data Lake.

• Data Storage and Management:Store and manage the data the ingested data. This involves optimizing data schemas and ensuring data quality and integrity.
• ETL (Extract, Transform, Load) Processes: Design ETL pipelines to transform raw data into a format suitable for analysis. This involves data cleansing, aggregation, and enrichment, ensuring the data is usable for data scientists and analysts.
• Code Review and Mentorship: Spend time reviewing code submissions from team members, providing feedback, and mentoring junior developers or team members on best practices and design patterns.
• Operational support: Perform operational work including troubleshooting and On-call rotation.
• Data Collection and Cleaning: Acquiring data from various sources and ensuring it is accurate, complete, and ready for analysis.
• Data Analysis and Interpretation: Analyzing large datasets using statistical and machine learning techniques to identify trends, patterns, and insights.
• Model Building and Evaluation: Developing predictive models using machine learning algorithms to solve business problems. This includes selecting the right algorithms, training models, and evaluating their performance.
• Data Visualization: Creating clear and impactful visualizations (charts, dashboards, reports) to present data findings to stakeholders.
• Collaboration: Working closely with cross-functional teams, including business analysts, engineers, and other stakeholders, to understand their needs and deliver data-driven insights.
• Testing: Designing and conducting A/B tests to validate hypotheses or test the effectiveness of various strategies.
• Data Strategy: Providing strategic advice on how to leverage data for business growth and decision-making, including identifying new data opportunities.
• Automation and Optimization: Streamlining data processes and automating repetitive tasks, ensuring efficiency in data pipelines and analytics workflows.
• Continuous Learning: Stay updated with the latest trends in software architecture, AI technologies, and development tools.
• Problem-Solving: Be available to troubleshoot and solve complex technical problems as they arise, offering expertise to resolve issues efficiently.
• Professional Development and Training: Participate in or conduct training sessions to enhance the team's skills and knowledge in specific areas related to application architecture and AI technologies.
• Performs other duties as assigned.
• Complies with all policies and standards.

Education/Experience:

A Bachelor's degree in a quantitative or business field (e.g., statistics, mathematics, engineering, computer science).
Requires 5 – 7 years of related experience.

Or equivalent experience acquired through accomplishments of applicable knowledge, duties, scope and skill reflective of the level of this position.

Technical Skills:

• Proficiency in Databricks platform
• Advanced data pipeline design and development
• Data quality and governance
• Machine learning model development and maintenance
• Data integration processes
• Data security and privacy regulations
• Data visualization tools development
• Data warehouse and data mart design and development
• ETL (Extract, Transform, Load) processes.
• Data governance and compliance
• Proficiency in SQL and Python
• Knowledge of Big Data technologies (Hadoop, Spark)
• Cloud computing (AWS, Azure, GCP)
• Data modeling and architecture
• Advanced analytics and predictive modeling
• Knowledge of data privacy laws and regulations
• Proficiency in BI tools (Tableau, PowerBI)
• Strong problem-solving skills
• Excellent communication and presentation skills
• Project management and team leadership.

Soft Skills:

• Intermediate - Seeks to acquire knowledge in area of specialty
• Intermediate - Ability to identify basic problems and procedural irregularities, collect data, establish facts, and draw valid conclusions
• Intermediate - Ability to work independently
• Intermediate - Demonstrated analytical skills
• Intermediate - Demonstrated project management skills
• Intermediate - Demonstrates a high level of accuracy, even under pressure
• Intermediate - Demonstrates excellent judgment and decision making skills
• Intermediate - Ability to communicate and make recommendations to upper management
• Intermediate - Ability to drive multiple projects to successful completion
• Intermediate - Possesses technical aptitude

License/Certification:

• CompTIA Security+ Certification, CISSP Certified Information Systems Security Professional, and/or Splunk Certifications preferred
• Databrick Certification, or Python Certifications(such as from Python Institute or Microsoft), or Professional Data Engineer(Google Cloud) orAWS Certified Big Data preferred

Pay Range: $100,900.00 - $186,800.00 per year

Centene offers a comprehensive benefits package including: competitive pay, health insurance, 401K and stock purchase plans, tuition reimbursement, paid time off plus holidays, and a flexible approach to work with remote, hybrid, field or office work schedules. Actual pay will be adjusted based on an individual's skills, experience, education, and other job-related factors permitted by law. Total compensation may also include additional forms of incentives.

Centene is an equal opportunity employer that is committed to diversity, and values the ways in which we are different. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other characteristic protected by applicable law.

Qualified applicants with arrest or conviction records will be considered in accordance with the LA County Ordinance and the California Fair Chance Act