AAIS is seeking an experienced Data Engineer who will focus on the design and development of our Data Lake/Warehouse environment, MDM platform, data analytics and data integration solutions. They must have a strong background in ETL, MDM, data modeling, and cloud architecture with the ability to undertake complex challenges and deliver measurable results.
You will work in an agile, collaborative and cross-functional environment with Actuaries, Software Architects, Operations, Product Developers and Customer Engagement. Core to this role is working with other Data Engineers and Analysts to innovate and deliver creative solutions to complex challenges.
- Govern – Architect solutions that ensure high data quality throughout the complete lifecycle of the data.
- Profile data – Analyze data to determine data quality, statistical validity, atomicity, and relationships by developing and utilizing various models (Kimball/Inmon, business-usable data sets, mining, etc.)
- Organize and Clean data - Organize and integrate data from disparate sources, including logical and physical data modeling
- Develop – build data integration applications that consistently and reliably process source data into business useable information in batch and real-time
- Analyze – Use various tools and techniques to analyze the data to answer specific business problems, discover unasked questions and opportunities, find relevance (statistical, predictive, etc.) across data, etc.
- Package – Develop data products for ongoing use by internal and external customers; prepare reports and presentations for AAIS leadership team to support your analysis.
- Define, organize, and self-manage data analysis projects under the leadership and strategic direction of the Director, Data Engineering.
- Design, develop and implement data mining tools and analyses/Data Modeling to sift through large amounts of data stored in a variety of formats (data warehouse, data marts, application or file sources) to find relationships and patterns.
- Maintain a working knowledge of data mining and visualization best practices and tooling.
- Collaborate with internal and external software developers, business analyst, etc. to define and actively develop data analytics solutions including data warehouse, ETL, MDM, data services, business intelligence front-ends, and dashboards.
- Clearly communicate methods and conclusions with simple language and innovative visualizations to management and executives.
- Design and implement world-class programs and automation to collect, process, integrate and analyze highly complex insurance experience and real-world data.
- Provide high-level expertise in analyzing and visualizing large, complex, and unique data sets. Facilitate the highest levels of efficiencies for all AAIS data users by understanding their business processes and applying the best data engineering strategies to their needs.
- Provide thought leadership in data management strategies, governance, and design.
What you will bring:
- Ability to quickly become an expert on AAIS’s data and industry position.
- Diverse knowledge and experience with data modeling and data warehousing.
- Experience with various business intelligence and analytics tools and concepts to transform raw data into useful information.
- Experience data governance and MDM patterns and implementations.
- Extensive hands on experience working with large structured and unstructured data sets, including statistical analyses, data visualization, data mining, and data cleansing/transformation.
- Experience prototyping and developing ETL solutions utilizing a variety of tools (Pentaho DI, Talend, scripting, PL/SQL, etc.) on a number of different data platforms (Oracle, MySQL, NoSQL, Hadoop).
- Entrepreneurial inclination to discover novel opportunities for applying analytical techniques to business problems across the insurance industry.
- Advanced skills in writing SQL queries and working with databases.
- Excellent written and oral communication skills; must be capable of fully yet concisely articulating technical concepts to non-technical audiences.
- The ability to manage multiple priorities in parallel and meet agreed upon deadlines by communicating and adjusting workload and expectations in collaboration with the Director, Data Engineering.
- Problem Solving/Critical Thinking skills: making the best decisions possible given the data quality and time available.
- Strong analytical thinking and ability to quickly pick up new methods, tools and domain expertise.
- Strong collaboration and mentoring skills.
- BS in Business, Math, Computer Science or other data engineering related discipline with 3+ years of data warehousing and analysis experience.
- 7+ years development experience on one or more Data Warehousing, Data Integration tools/languages and various Business Intelligence/Data Mining/Presentation Layer tools (reports, statistical analysis, dashboards, etc.).
- Hand-on experience with Hadoop technologies and management of data on Hadoop platforms. Bonus points for Hadoop administration experience.
- Significant exposure to, ongoing education and training in, and hands-on experience with Data Science concepts and practice including analytic methods and tools including models, time series, optimization, simulation, financial modeling, experimental design, etc.
- Demonstrable expertise in analytical models and leveraging data to make business decisions.
- Knowledge of BI best practices and a proven track record of delivering dynamic and powerful solutions.
- Experience following structured software development methodologies – Agile approaches preferred.
- Academic or industry experience with computational statistics and experience processing large quantities of data
- Experience in property and casualty insurance a plus.
- Bonus points for experience working with Actuaries, Actuarial models and/or data scientists.
- A record of success and top-tier achievement in prior work and education experiences.