Data Engineer
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Data Engineer

The person should interact directly with senior-level business executives of the client organization and understand the business requirements, collate, understand, and analyze the data, and prepare/build reports / automated dashboards. The reports / automated dashboards will be a judicious and effective mix of numerical tables (including appropriate statistical measures) and visualizations through charts/diagrams. The representation might require (re)defining metrics / KPIs or suggestions to the client about inadequacies in the data if such is the case. It would involve data cleaning, preprocessing, merging, integration from different sources.

Requisite Skills:

Technical:

Advanced level skill in python for data engineering – data cleaning, processing, report preparation using numpy, pandas, plotly, pymongo etc. by connecting to multiple data repositories (like RDBMS, Mongodb etc.).

Advanced level skill in writing functions/APIs in python and consuming APIs from different data sources for data integration (like Google, Salesforce etc.)

Working-Level skills with MS Power BI /Tableau including statistical analysis, geospatial representation of data, and connecting to multiple data repositories (like RDBMS, CSV files, etc.). Must have skills in creating automated dashboards

Working-level skills with MySQL (preferred, or other RDBMS) and writing SQL queries (select using primary and foreign keys, merge, joins, etc.) in some GUI front-end tools like MySQL Workbench or phpMyAdmin and big data like mongdb

Basic-level skills (Optional) with at least one GUI-based or workflow-based statistical / analytics tools like SPSS, Minitab, KNIME, Altryx

Working-level skills in BI reporting / statistical/mathematical / data science-related programming in Python. Some basic-level skills in visualization/graphics libraries (like ggplot2, plotly, etc) and app frameworks (like Python Dash, Flask, Django) is desirable and will be preferred

Basic-level skills in Javascript, HTML, CSS etc. for front-end BI/ML app development

Non-technical:

Fluent and excellent oral and written communication skills in English

Work in cross-functional and cross-cultural teams involving both technical and business members and stakeholders

Translating business requirements to technical requirements and explaining the outcome of technical analysis in an easily comprehensible manner to non-technical clients

Self manage work planning and time management to complete tasks / projects on time with excellent quality

Work Experience:

Between 3 to 5 years in a full-time data analysis/data engineering position applying most of the skills as indicated above

Academic Qualification:

Minimum graduation degree from a reputed university, preferably in STEM subjects like Mathematics, Economics, Computing etc.

Selection Process:

Personal interview with a strong emphasis on technical knowledge. It is highly desirable that the candidate is able to demonstrate some of his/her past work in the requisite skill areas.

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