Data Engineer {Python, SQL and ETL}  

The Data Engineer will focus on using various methods to design and implement an overall data infrastructure that will support current and future business needs. The data engineer is also tasked in creating data pipelines that transform raw data for analytical and operational processes.

Duties and Responsibilities:

-Design and build scalable big data infrastructure and solutions, leveraging available cloud resources
-Design, create and maintain ETL processes and data pipelines for functions such as but not limited to reporting and machine learning
-Collaborate with different cross functional teams to determine and satisfy business data requirements taking into account various technology stacks
-Optimize and automate existing current business processes and procedures
-Create and present ad hoc reports to key stakeholders

Job Qualifications:

-At least College Graduate
-With 2-3 years experience as Data Engineer
- Proficiency in Python
-Proficiency in data manipulation tools: Any of Pandas, Dplyr, Spark
-Experience with Extract, Transform and Load (ETL Processes)
-Experience in SQL and no SQl query languages
-Experience with any big data storage and processing solutions (SQL variants, MongoDb, Spark, Hive, Snowflake, Redshift, etc.)
-Experience with any cloud service or server based data processing.

Knowledge and skills:

• Proficiency in additional programming languages, particularly Pyspark, R, C++, Javascript, Java.
• Proficiency in AWS Cloud Services, particularly AWS Glue, AWS Lake Formation
• Familiarity with data warehousing services such as AWS Redshift, and Snowflake
• Familiarity in business intelligence tools: Any of Tableau, PowerBI, Quicksight, Google Data Studio.
• Familiarity in data visualization packages: Any of Dash, Plotly, Matplotlib, Ggplot, Folium.
• Familiarity in machine learning tools is a plus: Any of scikit-learn, caret, MATLAB, Julia.