Senior Data Engineer - LAM

Mid / Senior



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Lazard Asset Management (LAM) Technology is looking for Senior Data Engineer/Scientist with an understanding of the asset management industry. As a part of the Enterprise data team, the candidate will lead design, develop, testing, and implementing Data Lake platform. The role will be responsible to conduct data analysis, scripting, and updates for real-time and batch processing, Installing & configuration of the software tool, including hot fixes and upgrades. This role requires a highly motivated, organized and experienced developer with pride of ownership reflected through clean design, code quality and a disciplined software development approach.

Key Responsibilities:

  • Lead implementation of data strategy using enterprise data lake solution.
  • Spark and Python expert. Hands-on coding with the ability to outline solution design with coding best practices, perform code review and ensuring good and secure
  • Well-rounded technologist – Hands on experience with legacy and modern integration methods Data virtualization, ETL, and various data formats (e.g. JSON, XML, delimited, etc...
  • Possess a broad knowledge of Legal Entities that engage in financial transactions – Familiarity with building and mastering global identifiers, counterparty, Investment / Asset Types and Agreements, Standard Reference Data, Corporate hierarchies
  • Must be able to execute technical strategy to achieve a business vision, with input from multiple stakeholders (business, technology, data consumers) and drive the incremental completion
  • Communication skills –Strong presentation skills and the ability to articulate business, technical and project concepts to an audience at all levels of the organization, verbally and in writing, clearly, concisely and completely

Desired Qualifications:

  • 8+ years’ experience in Python or equivalent technologies (Scala, Perl) with excellent knowledge of pandas/numpy libraries specializing in data integration from multiple data sources using various ETL techniques and frameworks.
  • 5+ years’ experience with Spark/PySpark or equivalent distributed processing system.
  • 5+ years’ experience with SQL/T-SQL development and performance tuning
  • Experience with developing real time data pipelines using Kafka.
  • Experience in creating data service API for data consuming applications
  • BS / MS in Computer Science or Information Technology – equivalent experience accepted

Preferred additional skills:

  • Amazon AWS EMR or equivalent could architecture experience with a major cloud provider
  • Experience in distributed data storage that use parallel process or columnar data stores (E.g.: Presto, HBase, Druid)
  • Ability to apply and explain MDM concepts, data lifecycle management, etc.
  • Software Component mindset with a focus on quality, reuse, and testability

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