Job Description

About NationsBenefits:

==========================


At NationsBenefits, we are leading the transformation of the insurance industry by developing innovative benefits management solutions. We focus on modernizing complex back-office systems to create scalable, secure, and high-performing platforms that streamline operations for our clients. As part of our strategic growth, we are focused on

platform modernization

-- transitioning legacy systems to modern, cloud-native architectures that support the scalability, reliability, and high performance of core back- office functions in the insurance domain.


As a Data Engineer, you will be responsible for the Requirement Gathering, Data Analysis, Development and implementation of Orchestrated data pipeline solutions to support our organization's data-driven initiatives to ensure data accuracy and enable data-driven decision-making across the organization. The ideal candidate will possess a minimum of 3-5 years of hands-on experience in data engineer on high-performing teams. Expertise in DBT, Airflow, Azure Databricks, SQL, Python, Py-spark, Automation is a must and knowledge of reporting tools is addon.





Key Responsibilities:


3 to 5 years of hands-on experience using DBT. Airflow, Azure Databricks, Python, Py-spark and SQL , Preferred from Healthcare & Fintech Domain having Automation First Mindset. Hands-on experience with Data Collection, Data Analysis, Data modeling, Data Processing using DBT, Airflow, Azure Databricks, Py-spark, SQL, Python. Performance Optimization and Automation: Continuously monitor and optimize existing solutions and Debugging DAG failures and resolving. Data Processing: Leverage his expertise building Robust Data pipelines using mentioned tech stack with CI/CD. Collaboration: Collaborate with cross-functional teams, including data scientists, business analysts, and stakeholders, to understand their data needs and deliver solutions. Data Quality: Implement data validation and cleansing processes to ensure data accuracy, consistency, and reliability. Influence: bring right solution for use cases and convince the team to use. Open to Ad hoc Data Analysis and Reporting/Dashboard Development: Perform exploration data analysis, develop data visualizations, and generate actionable insights to support business decision-making. Stay Current: Stay up to date with emerging trends and technologies in data engineering and analytics and make recommendations for their adoption.

Requirements:


Bachelor's degree in computer science, Information Technology, or a related field. Minimum 3+ years of hands-on experience using DBT. Airflow, Azure Databricks, Py-spark, SQL, Python, Automation Flexible to build Data Reports and Dashboards using SQL, Python, Reporting Tools Strong Debugging and Automation skills Strong understanding of DWH/Data Lake concepts and methodologies. Experience with cloud platforms such as Azure, AWS or GCP Excellent communication, Presentation and interpersonal skills Knowledge of data quality, data Validation, data security and compliance standards is a plus. * Excellent problem-solving skills and attention to detail