Data Engineer

• Proven experience as a Data Engineer, Computer Science, Applied math, Mechanical Engineering, Industrial Engineering, or related quantitative field. Industry experience is preferred
• In-depth understanding of database management systems, online analytical processing (OLAP) and ETL (Extract, transform, load) framework
• Experience in programming languages such as Python, R, Scala, Java will be added advantage
• Experience with Visualization skills/tools (e.g. Microsoft Power BI, Qliksense, Tableau)
• Experience with GCP (BigQuery, Data Prep, Data Fusion)
• Knowledge of SAS, SQL queries, Alteryx
• Proven abilities to take initiative and be innovative approaches
• Strong oral, written and interpersonal communication skills
• Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations

Analytical mind with a problem-solving aptitude

Bachelors / Masters degree in Computer Science Engineering / Information Technology or an Engineering degree with MBA from a premier institute and quantitative emphasis

• Able to influence the strategic direction of the company by identifying opportunities in large, rich data sets to create and implementing data driven strategies that fuel growth including cost saving, revenue and profit
• Acquire deep understanding of the business problems and translate them into appropriate business solutions
• Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing actionable business results.
• Drive development and delivery of analytic and statistical models using skills such as data acquisition and management.
• Work with business partners using a collaborative, agile approach to develop solutions rapidly that add value and are centered around the user experience.
• Ability to develop optimization and creating Gen AI models to support business for their adhoc queries
• Designing, developing, deploying and maintaining business intelligence and analytics solutions that turn data into knowledge
• Presenting information through reports and visualization
• Translate business needs to technical specifications.
• Develop and update technical / implementation documentation.

Staying abreast of cutting-edge data science techniques, tools, and technologies, and continuously improving analytical capabilities: