Company Overview
Leading US Consultinig Company
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Leading US Consultinig Company
The Role
As the Big Data Technical Lead, you will be part of the technology solution team and bring the Big Data and Advanced Analytics capability to our smart platform. Work collaboratively with business partners, development managers, developers, and testers to facilitate new releases to the platform.
Responsibilities
Understanding business requirements and translating these into technical solutions based on the chosen platform and development the solutions.
Build and develop data model and establish data processing process specifications such as data extraction, cleaning, and verification, and OLAP multi-dimensional data analysis models.
Utilize Big Data technologies to design, develop, and evolve scalable and fault-tolerant distributed components
Responsible for the design and execution of abstractions and integration patterns (APIs) to solve complex distributed computing problems.
Managing processes for example Massively Parallel Processing (MPP) and validating information across multiple databases.
Skills Required
6-10+ years of overall IT experience with Big Data, Analytics, Data Warehousing and Business Intelligence development experience.
Experience in the set-up and administration of Hadoop, Spark platform and other related architecture components, working knowledge of tools like Hive, Spark, HBase, Sqoop, Impala, Kafka, Flume, MapReduce, Kylin, Superset etc.
Programming experience with Java, Scala and Python. Expertise with SQL and Data modeling and end to end design and build process of Near-Real Time and Batch Data Pipeline.
Work with highly diverse data and big data set in multiple types and formats, and sources.
Must be able to work with minimal supervision and interact with business/technical users as needed.
Understands the implication of security, compliance, and governance in data.
Deep understanding of building Big Data pipeline on Azure, AWS or Ali Cloud
Deep knowledge and development experience about Data Acquisition, Data Preparation, Big Data Analytics, Data Governance and Machine Learning.