Big Data Architect Resume Examples. Bad Data Analyst Resume Summary. Data Analyst Intern, Relishly, Mountain View April 2015 – Present. Transfer company business code (DIVCON) from Fortran to C++, and prepare the documentation. ), Strong experience on different data file formats (I.e. Cloudera, Hortonworks, Datastax), Experience with Big Data tools and technologies including working in a Production environment of a Hadoop Project, Extensive experience in Conceptual, Logical and Physical data modeling including new application data model design and maintenance, Experience developing Java RESTful Services using SpringBoot and Netflix OSS, Experience in leading or managing engineers is required, Professional experience implementing large scale secure cloud data solutions using Google data and analytics services e.g. And this is the result… Java Big Data Developer , 10/2018 to 05/2020 Trinet Group Inc. – Charlotte, NC Developed cluster-automation script for deploying kitchen templates (4 VM's – 24hrs validity) and standard 4 Node cluster. For more information on what it takes to be a Python Developer, check out our complete Python Developer Job Description. Developed and implemented algorithms for DTI Tensor Fitting with Camino and Python. Developed and designed e-mail marketing campaigns using HTML and CSS. Data Visualization: Matplotlib. ), Stream processing (Storm, Spark Streaming, etc. Now before you wonder where this article is heading, let me give you the reason of writing this article. Analyze customer’s data to build drug-like compound activity prediction model use statistical methods, such as, multivariate linear regression (MLR), etc. Wrote a program to monitor Virtual Machine performance data using VMWare API's. I hope this Big Data Engineer Resume blog has helped you in figuring out how to build an attractive & effective resume. Cluster maintenance activities such as patching security holes and updating system packages, Defining, evangelizing and supporting technology and business partners who use the platform, Advising on GDT technical decisions including architecture approach, solution design and detailed troubleshooting, Designing and deploying large scale distributed data processing systems, Implementing data intensive software product for network analytics, monitoring and troubleshooting, Willing to take on ownership of delivering solutions in cutting edge technologies, Distributing and centralising external research on insights & analytics, Providing technical leadership for technology teams delivering on the big data platforms, Resolving technical issues and advising on best practices for big data, Hadoop environments and AtScale, Driving successful installations of the product, configuration, tuning, and performance, Assisting with capacity planning for the environment to scale, Being meticulous about tracking things and follow-through, Managing team assignments by assessing subject area knowledge, individual capacity, and project demands, Evaluating candidates for new positions including FTEs & contractors, Understanding of the main causal inference concepts (A/B testing, treatment and control groups, inference on observational data), Analyzing/measuring the quality of data ingested into Cigna's Data Lake, Working knowledge of relational databases and SQL query tuning, Maintaining up-to-date organisation chart and global & market analytics & insights contacts, Launching internal SharePoint site, from content creation to communication, Establishing enterprise wide collaboration across functions, Working in collaboration with Accenture’s global network of experts and delivery centres, Setting up the technical framework for the technology and business teams, Participating in, map, design, implementation, unit test, performance, and regression test phases, Ensuring modularity, reusability and quality of designed and implemented components, Researching and evaluation of new tools and technologies to solve complex business problems, Managing a team of 5-7 FTE and 5-15 vendor resources (with frequent growth / mix changes) and provide feedback for individual contributor development, Coordinating with team to implement continuous process improvements, Ensuring the necessary and complete documentation is created, Working with production scale Machine Learning, Ensuring adherence to process and quality, and identifying project/program delivery risks and works on risk mitigation, Building marketing collaterals for Insurance specific solutions and share learnings across practices, Ongoing responsibility to manage the technology debt across the inventory of data services products, Applying the concept of continuous improvement, Work with the teams in facilitating architectural guidance, planning and estimating cluster capacity, and creating roadmaps for deployment, Engage in capacity planning and demand forecasting, anticipating performance bottlenecks and scaling the environment as needed, Develops and deploys solutions using data analysis, data mining, optimization tools, machine learning techniques and statistics, Responsible for designing and building new Big Data systems for turning data into actionable insights, Lead the engineering team responsible for the implementation and support of data ingestion, data processing and machine learning pipelines.

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