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Lazard Asset Management (LAM)
Technology is looking for 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
hotfixes 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.
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:
5+ 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.
3+ years’ experience with
Spark/PySpark or equivalent distributed processing system.
3+ 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
