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Responsibilities

• Work with members of the Navikenz/client teams building highly scalable distributed solutions that enable positive user experiences and measurable business growth
• Collaborate with/contribute to a cross-functional team including product and design as part of solution realization
• Collaborate with/Contribute to the team’s planning/design/implementation activities as part of solution realization
• Develop new features and infrastructure development in support of rapidly emerging business and project requirements
• Ensure application performance, uptime, and scale, maintaining high standards of code quality and thoughtful application design
• Design and implement scalable web services, applications, and APIs
• Develop and maintain internal software tools, accelerators, platforms
• Support, troubleshoot and debug software in production
• Identify bottlenecks, and improve continuously software performance, reliability, and overall quality
• Work with agile development methodologies, adhering to best practices and pursuing continued learning and improvement opportunities
• Participate in all aspects of agile software development including design, implementation, and deployment
• Create, maintain & improve design/technical documentation, manuals, how-to guides, etc.

Qualifications/Experience

The ideal candidate will have a bachelor’s or master’s degree in Computer Science or Software Engineering with at least 7 years of professional experience developing software across technology stacks – front-end to services to data:

• Backend feature, microservices and API development experience using Java or NodeJS
• Database knowledge to store and query data from either SQL or NoSQL databases
• Front end development experience with React or Angular along with HTML, CSS, and JavaScript
• Experience with cloud platform – Azure, AWS or GCP
• Experience designing SPAs that interact with REST API endpoints, converting mocks into high quality HTML/CSS
• Experience with design patterns, security, performance, and usability for both front end and backend
• Experience with CI/CD and automated unit testing
• Experience building large scale, high-available applications
• Excellent work ethic and strong sense of ownership of end results
• Creative problem solver and innovative thinker
• Ability to manage and lead a team of up to 10 members including Full Stack Developers, Test Engineers and deliver work to a well-defined plan
• Ability to work under indirect supervision
• Comfortable with ambiguity and time spent outside of comfort zone acquiring new skills
• Flexible in a fast-paced dynamic environment with shifting technologies, roles, and responsibilities

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.