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.