Job Location: Bangalore/Bengaluru
– Looking to hire a Senior Data Engineer with skills in Data Sciences (Python) & Data Engineering (Data Loading). Able to develop machine learning applications.
– As the Data Engineer, you will take structured, semi-structured and unstructured batch- and real-time data from numerous data sources, perform the relevant data cleansing and preparation, and build pipelines to support ingestion into strategic big data platforms, developing and testing the solutions in close collaboration with the business.
Responsibilities :
– The Data engineer is responsible for initiating, development & delivery of analytic solutions in an agile fashion to the business to provide insights & improvement to business processes.
– Engage directly with customers to design, develop and deploy AI enterprise applications on the C3 Platform
– Become an expert in application design and development on the C3 Platform. Lead design and code reviews of end-to-end customer applications
– Perform enhancement, testing and troubleshooting of applications based on the business needs.
– Continuously identify technical risks and gaps; devise mitigation strategies in anticipation of customer needs.
– Write specifications, documentation and user guides for customer applications.
– Designing and deploying Machine Learning algorithms for industrial applications such as fraud detection and predictive maintenance.
– Collaborating with data and subject matter experts from C3 and its customer teams to seek, understand, validate, interpret and correctly use new data elements.
– Driving adoption of Deep Learning models into next-generation of C3 products.
– The Data engineer uses data and their analytical ability to find and interpret rich data sources
– Manage large amounts of data; merge data sources; ensure consistency of datasets;
– Create visualizations to aid in understanding data; build mathematical models using the data; and present and communicate the data insightsfindings and produce and present results with dashboards
– Contribute to the exploration and understanding of new tools and techniques and propose improvements to the data pipeline.
– Integrate the operations data platform with analytical tools such as Spotfire, the Data Scientist workbench, the Data Marketplace, etc.
– Collaborate with Data Architects, Business partners, Data engineers and Data Scientists to understand data needs to drive key decision making throughout the company
– Implementing a solid, robust, extensible data warehousing design that supports key business flows.
– Performing all the necessary data transformations to populate data into a warehouse table structure that is optimized for reporting and analysis;
– Deploy inclusive data quality checks to ensure high quality of data
– Invent and simplify business processes to streamline workflows. Build and improve existing processes to ensure data integrity and efficient analyses
– Sourcing, analyzing trends, formulating projections, reporting quantitative data, performing ad-hoc analyses and evaluating business initiatives
– Experience in dealing with multiple sources of data and different APIs. Will be unifying messy APIs, extracting relevant data and linking it together with our static transit information.
Preferred Qualifications :
– Bachelor or master’s degree in information technology, computer science, business administration or a related discipline would be considered a strong benefit.
– Must have 5-7 years Java script programming experience (incl. Node.js)
– Advanced understanding and experience in web markup, including HTML5 and CSS3.
– Experience in React JS and Angular JS will be added advantage.
– Experience with prototyping languages such as Python and R will be added advantage.
– Also, formal training in SCRUM and other Agile techniques would be a distinct advantage.
– Experience in building and deploying AI-based enterprise applications
– Solid understanding of common Machine Learning techniques, applications.
Domain expertise in one or more of the following industries: Aerospace, Financial Services, Healthcare, Industrial Manufacturing, Oil & Gas, Public Sector, Power & Utilities, Supply Chain, Telecommunications
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