Data Engineer

at  Netstratum

Job ID
082024/41
Work Experience
3 - 5 years
Job Type
Full Time
Job Location
Middlesbrough , UK
Base Salary
As per company standards

JOB DESCRIPTION

Netstratum is looking for a Data Engineer with experience in Snowflake, you will be responsible for developing and implementing data-driven strategies and solutions to support our business objectives. You will work closely with cross-functional teams to analyze complex datasets, build predictive models, and generate insights that drive decision-making. Your expertise in Snowflake will be crucial for optimizing our data warehousing processes and ensuring data quality and accessibility. This role requires a proactive approach, leveraging predictive and prescriptive analytics to improve overall operational efficiency and customer outcomes

REQUIREMENTS:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; Master’s degree is a plus.
• 2+ years of experience as a Data Engineer or similar role, with a strong focus on Snowflake.
• Proficiency in Snowflake, including data warehousing, SQL, and ETL processes.
• Experience with data analysis tools and programming languages such as Python, R, or similar.
• Strong problem-solving abilities and experience with statistical analysis and machine learning.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Proven ability to work collaboratively in a fast-paced, team-oriented environment.
• Experience with other cloud platforms such as AWS, Azure, or Google Cloud.

• Utilize advanced statistical methods and machine learning algorithms to analyze large datasets, identify trends, and build predictive models.
• Design, develop, and maintain data pipelines and data warehousing solutions using Snowflake, ensuring optimal performance and efficient data storage and retrieval.
• Create compelling data visualizations and dashboards to effectively communicate insights to stakeholders.
• Collaborate with data engineers, business analysts, and other stakeholders to understand data needs and provide actionable insights.
• Ensure data accuracy and integrity by implementing robust data validation and cleansing processes.
• Continuously assess and improve data processes and workflows to enhance efficiency and scalability.
• Document data processes, models, and methodologies to ensure transparency and facilitate knowledge sharing within the team.