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Responsibilities

• • Act as a subject matter expert in data engineering and GCP data technologies.
  • Work with client teams to design and implement modern, scalable data solutions
    using a range of new and emerging technologies from the Google Cloud Platform.
  • Work with Agile and DevOps techniques and implementation approaches in the
    delivery.
  • Be required to showcase your GCP Data engineering experience when
    communicating with clients on their requirements, turning these into technical data
    solutions.
  • Be required to build and deliver Data solutions using GCP products and offerings.

Requirement/Experience

• • The ideal candidate will have a Bachelor’s, Master’s Degree in Mathematics or Computer
    Science with around 6 to 7 years of professional experience working on data sets and
    building data pipelines. Briefly, he should have
  • Master’s degree in Computer Science, or related field.
  • Hands on and deep experience working with Google Data Products (e.g. BigQuery,
    Dataflow, Dataproc, AI Building Blocks, Looker, Cloud Data Fusion, Dataprep, etc.).
  • Experience in Data Integration, Data Transformation, Data Quality and Data Lineage
    tools.
  • E2E Data Engineering and Lifecycle (including non-functional requirements and
    operations) management.
  • E2E Solution Design skills – Prototyping, Usability testing and data visualization
    literacy.
  • Experience with SQL and NoSQL modern data stores.
  • Understanding of Big Data technologies and solutions (Spark, Hadoop, Hive,
    MapReduce) and multiple scripting and languages (YAML, Python).
  • Demonstrable track record of dealing well with ambiguity, prioritizing needs, and
    delivering results in a dynamic environment.
  • Excellent verbal and written communication skills with the ability to effectively
    advocate technical solutions to research scientists, engineering teams and business
    audiences.
  • Liaise and be part of our extensive GCP community, contributing in the knowledge
    exchange learning programme of the platform.
  • Ability to lead a team of data engineers to build pipeline for atleast 2 projects

Responsibilities

• • Act as a subject matter expert in data engineering and GCP data technologies.
  • Work with client teams to design and implement modern, scalable data solutions
    using a range of new and emerging technologies from the Google Cloud Platform.
  • Work with Agile and DevOps techniques and implementation approaches in the
    delivery.
  • Be required to showcase your GCP Data engineering experience when
    communicating with clients on their requirements, turning these into technical data
    solutions.
  • Be required to build and deliver Data solutions using GCP products and offerings.

Requirement/Experience

• • The ideal candidate will have a Bachelor’s, Master’s Degree in Mathematics or Computer
    Science with around 3 to 4 years of professional experience working on data sets and
    building data pipelines. Briefly, he should have
  • Master’s degree in Computer Science, or related field.
  • Hands on and deep experience working with Google Data Products (e.g. BigQuery,
    Dataflow, Dataproc, AI Building Blocks, Looker, Cloud Data Fusion, Dataprep, etc.).
  • Experience in Data Integration, Data Transformation, Data Quality and Data Lineage
    tools.
  • E2E Data Engineering and Lifecycle (including non-functional requirements and
    operations) management.
  • E2E Solution Design skills – Prototyping, Usability testing and data visualization
    literacy.
  • Experience with SQL and NoSQL modern data stores.
  • Understanding of Big Data technologies and solutions (Spark, Hadoop, Hive,
    MapReduce) and multiple scripting and languages (YAML, Python).
  • Demonstrable track record of dealing well with ambiguity, prioritizing needs, and
    delivering results in a dynamic environment.
  • Excellent verbal and written communication skills with the ability to effectively
    advocate technical solutions to research scientists, engineering teams and business
    audiences.
  • Liaise and be part of our extensive GCP community, contributing in the knowledge
    exchange learning programme of the platform.
  • 5+ years of relevant experience in Data Engineering using GCP

Responsibilities

• Lead a team of data scientists and ML engineers for program executions
• Teach, lead, and counsel colleagues on new techniques or solutions
• Collaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the company’s ecosystem
• Provide support to data science team with high-level expertise in an open-source language (e.g., R, Python, Julia, etc.)
• Spot and evaluate emerging/cutting edge, open source, data science/machine learning libraries/big data platforms (e.g. XGBoost, H2Oai, Spark, Hadoop, etc.)
• Work on papers to publish problem solving approach with ML Models, NLP and Computer vision techniques
• Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques
• Utilize data visualization tools to deliver insights to stakeholders.
• Prepare, maintain and present clear and coherent communication, both verbal and written, to understand data needs and report results
• Working with the Navikenz Solution Architect, build/operationalize the defined solution to be scalable, maintainable and production-ready
• Conduct research and develop prototypes and proof of concepts

Qualifications/Experience

The ideal candidate will have a Bachelor’s, Master’s degree or PhD in Statistics, Mathematics, Computer Science or another quantitative field, with at least 5 years of professional experience manipulating data sets and building statistical models, and familiar with the following software/tools/techniques (overall 10 years of experience):

• Combined knowledge of computer science and applications, modeling, statistics, analytics and maths to solve problems
• Knowledge and experience in statistical, machine learning algorithms and techniques: Regression, Classification, Random Forest, Boosting, Decision Trees, text mining, social network analysis, neural networks, etc.
• Coding knowledge and experience with several languages: Python/R/Julia, Java/Javascript, REST, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Databricks, H2O.ai, etc.
• Experience visualizing/presenting data for stakeholders using: Matplotlib, ggplot, D3, etc.
• Experience with cloud based platforms/products – AWS, Azure, GCP, Kubeflow, AutoML etc.