Big Data Platforms & Strategy

  Data-driven evaluations and designs of large-scale data processing systems.
  Setup of cloud-based systems for data ingestion, transformation, and analytics, including machine learning.
  Creation of dashboards and visualizations of key information for stakeholders.

Enterprise Data Governance & Security

  System auditing and security recommendations.
  Creation of enterprise-wide knowledge bases and centers of excellence.
  Systems auditing and security recommendations (PII/GDPR/CCPA).

Virtualization & Microservices

  Experience delivering secure and scalable microservices architectures using Kubernetes.
  Leveraging Docker-powered containerized architectures for large-scale distributed computing and processing.
  Delivering hyperscaler-agnostic solutions that work on Azure, AWS, Google Cloud.
  Providing secure environments using mutual Transport Layer Security.

Machine Learning & Predictive Analytics

  Skilled at both supervised and unsupervised machine learning techniques, using state-of-the-art tools and libraries.
  Able to match heterogeneous data at scale to link datasets for analytics and insight discovery.
  Experts in creating effective Data Science teams.
  Track-record of building production-quality ML pipelines.


Discovery & Requirements

Understand the vision and requirements.

Design & Architecture

Design and architecture, platform strategy and go-forward plan.

Implementation & Support

Coding, analytics, deployments, CI:CD pipelines, and support phase.

Success Stories

Media Conglomerate


  Large media company with portfolio of content across many distribution platforms (e.g., streaming, over-air).


  They needed help migrating their big-data processing solutions to the cloud and setting up analytics / ML.


  Our team rapidly gathered requirements and performed a cloud-provider comparison evaluation.


  Resulted in the setting up a new EMR-based solution on AWS that included data ingestion, transformation, analytics, data science and reporting capabilities.
  We also helped scale client’s in-house development team and expertise by ~20 new resources.

Series B Startup


  Rapidly-growing startup focused on data governance and classification issues (e.g., GDPR, PII, CPNI).


  They needed help architecting and scaling their V1 platform to accommodate new customers on the cloud.


  Our team architected a containerized and secure microservices-based solution.


  Resulted in the deployment of a Kubernetes-based & cloud-agnostic solution that could also integrate with on-prem resources.
  We also improved client’s development processes and agility by instituting automated deployment systems and policies (CI:CD pipelines).

Shipping & Logistics Company


  Large logistics company was acquiring a foreign subsidiary in a complimentary market segment.


  They needed an evaluation of the target company’s technology stack for their private equity due diligence.


  Our team developed a strategy for measuring and testing different aspects of their infrastructure and software systems.


  Resulted in the execution of a series of comprehensive integration and user tests that would ensure acquired technology would add value to the new company.
  We also proposed an integration roadmap and growth plan for the combined technology stack of the post-merger company.

Telecom Provider

  National telecom provider with large array of diverse customer data across multiple data warehousing systems.


  They needed help addressing enterprise data security and governance, both from a technical and policy-level.


  Our team reviewed their internal audit results and prepared an enterprise-wide plan for data security.


  Resulted in data security policies across Hadoop and Teradata systems, including user-auditing and row-level table encryption.
  We also proposed a strategy for a new enterprise-wide Center of Excellence for big data & security topics.


  Design hypothesis tests, oversee test execution, and evaluate the results.

  Develop metrics to measure business performance.

  Model, predict, and classify consumer behaviour and other business metrics.

  Utilize machine learning and large-scale data mining techniques to discover and identify actionable patterns in the data.

  Applicants must have at least 3 years’ experience in performing data analysis / predictive modelling.

  Well-developed quantitative skills and analytical thinking.

  Ability to query databases and perform basic statistical analysis.

  Strong understanding of statistics and statistical theory.

  Expertise in working with data platforms including those involving large scale data: SQL, Hadoop, PL/SQL, Pig, Hive, etc.

  Technical expertise in working with a language of your choice: Perl, Python, Java, or Ruby.

  Familiarity with hypothesis testing and study design.

  Proficiency in SAS and SQL.

  Prior practical experience in techniques such as SVM, Predictive modelling, and Self-learning systems.

  A domain background in ecommerce, healthcare, or telecom will be a plus.

  Turn large data sets into progressive ideas through the creation of clear, compelling infographics, maps, data visualizations, and interactive media and product designs.

  Develop rich interactive graphics, data visualizations of "large" amount of structured data, preferably in-browser.

  Model, predict, and classify consumer behaviour and other business metrics.

  Lead the complete lifecycle of visual analytical applications, from development of mock ups and storyboards to the complete production-ready application.

  Interface with data miners and analysts to extract, transform, and load data from a wide variety of data sources.

  Fluent in JavaScript & HTML5/Canvas.

  Fluent in one server side language: Java, C/C++, PHP, Python, Perl, Node.js, etc.

  Experience with Data Visualization tools/toolkits: Pentaho, Tableau, D3, Saiku, Vislt, ParaView, Protoviz, Maya, 3D Studio, etc.

  Ability to build what you design.

  Exemplary organizational, presentation and communications skills.

  Exceptional analytical and problem-solving skills.

  Ability to work with multiple groups across reporting lines.

  Experience in developing many different types of visualizations, including visual analytics; real-time visualization for situation awareness; visualizations for interactive data exploration; narrative / editorially-guided visualizations; time series analysis methods.

  Understanding of statistical methods, including statistical process control.

  Minimum 3 years of experience with JavaScript and front end visualizations.

  Minimum 1 year of experience working in the field of data visualization.

  BA, BFA, MFA in the following Fine Arts: Studio Art, Graphic / Visual Design, Visual Communications, or equivalent professional experience is preferred.

  Be a strong technology leader for the organization.

  Manage the design and architecture for large complex projects or programs.

  Develop overall solution for the engagement based on client’s future business needs, industry best practices, and inputs from internal teams (process, functional, technical).

  Share industry best practices and defines the framework for reuse, automation, and architecture assurance.

  Interact with CIO and Senior Management from client organization.

  Expertise in mapping IT strategy to business strategy.

  Experience in two or more areas: Business architecture, Application architecture, Information architecture, Technology and Infrastructure architecture.

  Expertise in enterprise information/data architecture involving both structured and unstructured data.

  Experience in designing and implementing large scale data architectures.

  Experience in Big Data technologies: Hadoop (Hortonworks, Cloudera, or MapR), Spark, RedShift, Azure SQL Data Warehouse.

+1 425-598-3006

127 Bellevue Way SE, Suite 106, Bellevue, WA 98004, United States

7/1, Viswanathar Koil Street, St. Thomas Mount, Chennai, TN 600016, India

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