Data Engineer - SQL and Python (ASAP)
Summary
Designs and builds scalable big data infrastructure and ETL/data pipelines that transform raw data for reporting, machine learning, and operational processes, while collaborating with cross-functional teams and automating business processes. Core stack: Python, SQL/NoSQL, big data tools (Spark, Hive, Snowflake, Redshift, MongoDB) and cloud services.
GENERAL RESPONSIBILITIES:
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 SPECIFICATIONS:
Education – At least graduate with a Bachelor’s or Master's Degree in IT, Computer Science, Engineering, or any related course.
Related Work Experience
- 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 noSQL 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