VP - Big Data and ETL Engineering

Marsh & McClennan is seeking candidates for the following position based in New York or Phoenix

VP - Big Data and ETL Engineering

What can you expect?

The role drives business and technical capability development and execution in our Digital Platforms space. The candidate will play a key hands-on role on the Big Data team as part of Marsh Digital and will partners with Product Owners, Enterprise Architects, Infrastructure Engineering, Scrum Masters, Business Partners, and external service providers to identify and execute future capabilities and influence strategies to enhance the Big Data platform.

What is in it for you?

• This role will work on next generation data platform services and processes that support Business to Business (B2B) and Business to consumer (B2C/B2B2C) applications.
• The role is expected to challenge the teams to think differently to achieve desired business outcomes and foster a culture of quality
• Competitive Benefits
• Career Development opportunities

We will Count on you to:

• Design and build scalable infrastructure and platform to ingest, store and process very large amounts of data (structured, semi-structured and unstructured), including streaming and real-time into the cloud based Big Data Lake
• Build best in class ETL/ELT based solutions for effective data ingestion and transformation
• Collaborate with the various technical, platform and product development team on the use of various AWS services, including Amazon Elastic Compute Cloud (EC2), S3, Elastic Map Reduce (EMR), Kinesis, ElasticSearch, Glue, Athena etc.
• Work closely with the IT and the platform team to deliver technical solutions. This includes end to end data orchestration, data layering, data governance, metadata management and data cataloging
• Be an expert in all things data including data wrangling, aggregation, summarization and analysis
• Collaborate with the various data source teams both internal and external(Oracle, Teradata, MongoDB, cloud etc.) on effective strategies for data ingestionPartner with the data science, actuarial science and various business group on deep rooted data analysis including propensity scores, catastrophic modeling, time-series analysis and forecasting

• Be an evangelist for all things Big Data and Digital

What you Need to Have:

• Bachelor's Degree in Computer Science, Mathematics, Engineering or Statistics. Master's Degree a definite plus
• 5-10 years of overall data, systems development and integration experience
• 2-5 years of relevant Data Ingestion/ETL/ELT, Big Data and Data Visualizations experience of mission critical platforms
• Experience in ETL/ELT and data wrangling using tools (Informatica, Talend etc.) and languages such as Python, R, Scala, Java, SQL and SAS
• Experience in Hadoop and Big Data platforms including cloud based platforms such as AWS, Azure & GCP.
• Experience in various services such as Hive, EMR, Juypter notebooks, Kinesis, SQS, Glue, Athena, Kafka, Redis, MongoDB etc.
• Knowledge of Statistics, Operations Research and Machine/Deep Learning algorithms a definite plus
• Ability to work in a fast-paced environment both as an individual contributor and a technical lead
• Prior hands-on experience delivering self-service big data and data visualization platforms

Marsh is the world's leading insurance broker and risk adviser. With over 35,000 colleagues operating in more than 130 countries, Marsh serves commercial and individual clients with data driven risk solutions and advisory services. Marsh is a business of Marsh & McLennan Companies (NYSE: MMC), the leading global professional services firm in the areas of risk, strategy and people. With annual revenue approaching US $17 billion and 76,000 colleagues worldwide, MMC helps clients navigate an increasingly dynamic and complex environment through four market-leading businesses: Marsh, Guy Carpenter, Mercer, and Oliver Wyman. Follow Marsh on Twitter @MarshGlobal; LinkedIn; Facebook; and YouTube, or subscribe to BRINK.

Marsh & McLennan Companies and its Affiliates are EOEMinority/Female/Disability/Vet/SexualOrientation/Gender Identity employers.