The Data Engineer will focus on the design and development of our Data Lake/Warehouse environment, analysis platforms and ETL pipelines which deliver rich business analytics and empowers the organization through actionable insights.
You will work in an agile, collaborative and cross-functional environment with 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.
- Discover data - Identify internal and external sources of data to enable and enhance business intelligence efforts and data product revenue
- 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 ETL 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 for 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 products.
- Collaborate with internal and external software developers, business analyst, etc. to define and actively develop data analytics solutions including Data Warehouse, ETL, Reports, Analytics, 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.
What You Will Bring
- Ability to quickly become an expert on AAIS’s data and industry position.
- Knowledge and experience with data modeling and data warehousing.
- Experience with business intelligence tools and concepts to transform raw data into useful information.
- Hands on experience working with large structured and unstructured data sets, including data visualization 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.
- 2+ 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.
- 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
- A record of success and top-tier achievement in prior work and education experiences.
Resumes forwarded to: email@example.com