Chubb is the world's largest publicly traded property and casualty insurer. With operations in 54 countries, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance, and life insurance to a diverse group of clients. Chubb is also defined by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength, and local operations globally.
Data is at the core of our business. The data engineer is a technical job that requires substantial expertise in a broad range of software development and programming fields. The data engineer should especially have sufficient knowledge of big data solutions to be able to implement those on the premises or in the cloud.
A data engineer generally works on implementing complex big data projects with a focus on collecting, parsing, managing, analyzing, and visualizing large sets of data to turn information into insights using multiple platforms. He or she should be able to decide on the needed hardware and software design needs and act according to the decisions. The big data engineer should be able to develop prototypes and proof of concepts for the selected solutions.
The ideal candidate for this role is someone with a strong background in computer programming, statistics, and data science who is eager to tackle problems with large, complex datasets using the latest Python, R, and/or PySpark. You are a self-starter who will take ownership of your projects and deliver high-quality data-driven analytics solutions. You are adept at solving diverse business problems by utilizing a variety of different tools, strategies, algorithms, and programming languages.
Specific responsibilities are as follows:
- Utilize the data engineering skills within and outside of the developing Chubb information ecosystem for discovery, analytics, and data management
- Work with the data science team to deploy Machine Learning Models
- You will be using Data wrangling techniques to convert one "raw" form into another including data visualization, data aggregation, training a statistical model etc.
- Work with various relational and non-relational data sources with the target being Azure-based SQL Data Warehouse & Cosmos DB repositories
- Clean, unify and organize messy and complex data sets for easy access and analysis
- Create different levels of abstractions of data depending on analytics needs
- Hands-on data preparation activities using the Azure technology stack, especially Azure Databricks are strongly preferred
- Implement discovery solutions for high-speed data ingestion
- Work closely with the Data Science team to perform complex analytics and data preparation tasks
- Work with the Sr. Data Engineers on the team to develop APIs
- Sourcing data from multiple applications, profiling, cleansing, and conforming to create master data sets for analytics use
- Utilize state-of-the-art methods for data manning especially unstructured data
- Experience with Complex Data Parsing (Big Data Parser) and Natural Language Processing (NLP) Transforms on Azure a plus
- Design solutions for managing highly complex business rules within the Azure ecosystem
- Performance tune data loads
Qualifications
- Mid to advanced level knowledge of Python and Pyspark is an absolute must.
- Knowledge of Azure, Hadoop 2.0 ecosystems, HDFS, MapReduce, Hive, Pig, sqoop, Mahout, Spark etc. a must
- Experience with Web Scraping frameworks (Scrapy or Beautiful Soup or similar)
- Extensive experience working with Data APIs (Working with RESTful endpoints and/or SOAP)
- Significant programming experience (with the above technologies as well as Java, R, and Python on Linux) a must
- Knowledge of any commercial distribution like HortonWorks, Cloudera, MapR etc. a must
- Excellent working knowledge of relational databases, MySQL, Oracle etc.
- Experience with Complex Data Parsing (Big Data Parser) a must. Should have worked on XML, JSON and other custom Complex Data Parsing formats
- Natural Language Processing (NLP) skills with experience in Apache Solr, and Python a plus
- Knowledge of High-Speed Data Ingestion, Real-Time Data Collection and Streaming is a plus
Qualifications/Experience
- Bachelors in Computer Science or related educational background
- 3-5 years of solid experience in Big Data technologies a must
- Microsoft Azure certifications a huge plus
- Data visualization tool experience a plus
EEO Statement
At Chubb, we are committed to equal employment opportunity and compliance with all laws and regulations pertaining to it. Our policy is to provide employment, training, compensation, promotion,and other conditions or opportunities of employment, without regard to race, color, religious creed, sex, gender, gender identity, gender expression, sexual orientation, marital status, national origin,ancestry, mental and physical disability, medical condition, genetic information, military and veteran status, age, and pregnancy or any other characteristic protected by law.Performance and qualifications are the only basis upon which we hire, assign, promote, compensate, develop and retain employees. Chubb prohibits all unlawful discrimination, harassment and retaliationagainst any individual who reports discrimination or harassment.
