Senior Business Intelligence Engineer
The Senior Business Intelligence Engineer solves complex business problems and issues using data from internal and external sources to provide insight to decision-makers. The Senior Business Intelligence Engineer work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors.
The Sr. BI Engineer Implements complex data ingestion and transformation processes with a focus on collecting, parsing, managing, analyzing, and visualizing large sets of structured and unstructured data sets that produce valuable business insights and discoveries. The Sr. BI Engineer works closely with data scientists, data engineers, database administrators and architects to determine the data needs and methods to make them available to the analytics team. Empowers the team of analysts and data scientists to deliver data driven insights and applications to GBO and Employer group stakeholders.
- Work with business partners and data science teams to understand business context and Insights being pursued
- Build data ingestion solutions to extract, consolidate, transform structured and unstructured data from a variety of data sources (internal and external as needed) and create/load to existing and new Data Lakes to be used for Analytics and BI/Reporting initiatives supporting GBO/Group business.
- Create robust and automated pipelines to ingest and process structured and unstructured data from source systems into analytical platforms using batch and streaming mechanisms leveraging cloud native toolset to support Real-time Analytics needs and Machine Learning
- Work with data scientists to operationalize and scale machine learning training and scoring components by joining and aggregating data from multiple datasets to produce complex models and low-latency feature store
- Lead collaboration with “Digital Health & Analytics” (DH&A) Unit and IT to help build a scalable next gen Cloud platform to so support data transformation, ML and AI Strategy.
- Lead and guide the evolution of various data management functions (Data Catalog, Data Prep, Data Lineage & Metadata Management functions)
- Provide hands-on technical leadership in all aspects of data engineering design and implementations including data ingestion, data models, data structures, data storage, data processing, and data monitoring at scale
- Evaluate and make recommendations on new technologies, tools and guide the team on up-to-date technologies, standards, and practices
- Coach and mentor more junior resources
- Contribute to the internal knowledge base to build expertise and awareness within the organization
- Assist in our recruiting and interviewing process
- Participate in developing projects plan, timelines and providing estimates
- Participate in daily scrum calls and provide clear visibility to work products
- Bachelor's degree in Computer Science, Mathematics, Statistics, Business Analytics or Engineering.
- 4+ years of software engineering experience with object-oriented design, coding and testing patterns, as well as, experience in commercial or open source software platforms and large-scale data infrastructures.
- 3+ years of experience in building enterprise scale BI solutions using Power BI, Tableau
- 2+ years of experience with programming languages like Python or Scala
- Solid hands-on experience in Data modeling and various schemas
- Strong ETL development experience using technologies and tools like Flume, Spark, Oozie etc, SQL programming
- Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
- Experience with Big Data Machine Learning (ML) toolkits, such as Mahout, SparkML, or H2O
- Experience building mechanisms for near-real time data delivery solutions to analysts and data scientists who create insights and analytics applications for our stakeholders
- Solid experience in communicating Insights to business leaders in Business-friendly manner
- Master’s degree in Computer Science, mathematics or Engineering
- Demonstrable experience in Health Insurance domain, familiarity with Products, Claims processing,
- 2+ years experience developing and implementing enterprise-level data solutions utilizing Python (Scikit-lean, Scipy, Pandas, Numpy, Tensorflow) , Java, Spark, and Scala, Airflow , Hive, REST APIs, JSON, XML, and micro service architectures
- 2+ year of experience working on Big Data Processing Frameworks and Tools – Map Reduce, YARN, Hive, Pig, Impala, Oozie, Sqoop, and good knowledge of common big data file formats (e.g., Parquet, ORC, etc.)
- Certification –preferably Azzure or AWS Certified Big Data or any other cloud data platforms, big data platforms
- Experience in implementing machine learning pipeline.
- Experience with Vertica
- Kubernetes and Docker experience a plus
- Prior working experience on data science
- Cloud data warehouse experience
- Experience with NoSQL databases such as HBase, Cassandra, MongoDB
- Experience with Cloudera/MapR/Hortonworks