Data Engineer I

Mercury Insurance Services LLC/MIS is an insurance organization seeking a Data Engineer I. The role focuses on building big data and data lake solutions, solving data integration challenges, optimizing production processes, and collaborating with analytics and data science teams to support business and regulatory objectives.

Responsibilities:

• Design, build, and launch collections of high-quality big data/data lake solutions on Cloud platform preferably AWS, that support multiple use cases across all departments, all products, and all states
• Solve our most challenging data integration problems, utilizing optimal ETL patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
• Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
• The Data Engineer is an expert in all data lakes, data warehouses, and data cubes within Mercury, with no gaps in knowledge. Can efficiently and accurately extract and manipulate data from any source
• Collaborate with teams of data analysts and data scientists, who research and integrate algorithms to develop solutions to address complex data problems. Influence all functions across the organization to identify data opportunities to drive profitable growth. Proactively identify pain points that Analytics & Data Science face with our existing data models
• Leverages existing data infrastructure to fulfill all data-related requests, perform necessary data housekeeping, data cleansing, normalization, hashing, and implementation of required data model changes. Analyzes data to spot anomalies, trends and correlate similar data sets. Designs, develops and implements natural language processing software modules
• Other functions may be assigned

Requirements:

• Bachelor's degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, Information Systems, or related field OR equivalent combination of education and/or experience
• 1 or more years of experience in data analytics, data engineering, and/or data science
• 1 or more years of experience in architecting/designing and leading development of big data/data lake solutions on Cloud platforms, preferably AWS (S3, Glue/EMR, Athena, AppFlow)
• 1 or more years of experience in Python or Java programming
• 1 or more years of experience in writing SQL statements and query performance tuning
• 1 or more years of experience in RDMS or MPP databases, preferably AWS Redshift or Snowflake
• A high-level specialist who regularly interacts and works with senior management
• Expert at analyzing data to identify gaps and inconsistencies
• Able to multitask, prioritize, and manage time effectively
• The ability to think conceptually, analytically and creatively comfortable with ambiguity
• Experience managing and communicating data plans and data models to internal clients
• Demonstrated solid understanding, and passion for, all areas of data/analytics engineering best practices
• Demonstrated expert skills in data mining and data analytics
• Expert in Python and/or SQL programming
• Solid experience with cloud-based advanced data and analytics environment
• Knowledge of working with AWS, GitHub, and other cloud-based infrastructure
• Expert data skills and the ability to work with large structured and unstructured data sources
• Excellent problem-solving skills required
• Excellent analytical and critical thinking required
• Excellent written and verbal communication skills required
• Demonstrate Company's Core Values
• Experience supporting or building cloud-based data platform workflows in AWS, including services such as S3, Lambda, Docker, and EKS
• Experience working with Spark for large-scale data processing, transformation, or dataset preparation within a data lake or big data platform environment
• Exposure to data ingestion or integration pipelines, including working with internal and external application data, vendor API calls, and enabling secure data delivery into a data lake environment
• Familiarity with CI/CD practices and cross-functional infrastructure support, including partnering with teams such as Infrastructure, DBA, and platform administration to provision and maintain access, environments, and orchestration tooling
• Exposure to AI and automation
• Create and Maintain Libraries - Proficiency in creating and maintain libraries to enhance automated capabilities
• Coding Skills - Strong knowledge of programming languages commonly used in automation, such as Java or Python
• Release Process and Continuous Integration/Continuous Deployment (CI/CD) - Proficiency agile software development release process, CI/CD practices and tools (e.g., Jenkins, GitHub) to integrate automated tests into the build process
• Debugging and Troubleshooting - Strong skills in diagnosing issues and scripts to ensure smooth operation
• Best Coding Practices - Ability to follow best practices and receive constructive feedback
• Documentation Skills - Proficiency in documenting components, usage instructions, presentation, and bug report, etc
• Continuous Learning - Commitment to staying updated with the latest trends, tools, and technologies
• Attention to Detail - Meticulous attention to detail to ensure high-quality reliable framework performance
• Multi-Tasking Skill with Positive Attitude - Multi-Tasking skill with willingness and positive attitude to do whatever it takes to complete tasks on time or as quickly as possible
• Time Management - Excellent organizational skills to manage multiple testing projects, prioritize tasks, and meet deadlines
• Adaptability and Flexibility - Ability to adapt to new tools, new approach, new process in a fast-paced development environment