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NCS Philippines is seeking a Data Engineer to design and implement scalable data infrastructure and data pipelines to support business analytics and operations.
The role involves building ETL processes, collaborating with cross-functional teams, and delivering ad hoc reports. Strong Python, SQL, and cloud data warehousing experience are required for this position.
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.