Data Engineer [ASAP Starter Only!]

NON-NEGOTIABLE REQUIREMENTS:

• Project A: Python, SQL, ETL/Data Flows

• Project B: Snowflake, BigQuery, GCP

• At least 2 years work experience

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

FUNCTIONAL/TECHNICAL COMPETENCIES:

Data Modelling and Design, Data Management, Data Visualization, Programming/Software Development, Analytics.

CORE COMPETENCIES:

Teamwork & Collaboration, Accountability, Customer Focus, Communication, Innovation, Quality

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

• Knowledge and Skills – Knowledgeable in the following:

  • 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.