Data Engineer

at  Tyde Digital

Tyde Digital, a trusted business optimization consultancy, is looking for a highly analytical and detail-oriented Data Engineer to join our rapidly growing team.
At Tyde, we collaborate with businesses across diverse industries and regions, helping them enhance four key areas of their operations— people, processes, technology, and data. Our goal is to empower organizations with data driven decision-making, enabling them to achieve their strategic objectives.
As a Data Engineer, you’ll play a pivotal role in designing, managing, and optimizing data infrastructure. You’ll work closely with Business Analysts and Data Analysts to transform complex data into actionable insights, driving meaningful and measurable outcomes for our clients.

REQUIREMENTS

• Bachelor’s degree in a relevant field (e.g., Computer Science, Data Science, Information Technology) or equivalent experience.
• 3+ years of experience in data engineering or a related role.
• Proven experience in data engineering or a related role.
• Proficiency in data pipeline development, including ETL processes.
• Strong programming skills in languages such as Python, C#, or Java.
• Experience in extracting applicable data from databases using SQL.
• Experience in cloud computing platforms (AWS/GCP/Azure).
• Experience with BI tools like Power BI, Tableau, or similar platforms.
• Strong problem-solving abilities and attention to detail.
• Ability to work collaboratively in a cross-functional team environment.
• Knowledge of data governance and security best practices is a plus.
• Excellent verbal and written communication skills.
• Excellent data visualization and communication skills.
• Experience with Power Platform Development applications.
• Experience with custom SharePoint applications and workflows (Shell).

• Data Pipeline Development: Design and implement scalable and efficient architecture for data pipelines, ensuring seamless data flow across multiple endpoints.
• Technical Customizations: Deploy technical customizations to pre-packaged software solutions.
• Micro-service and API Development: Create and deploy micro-services and APIs to facilitate data transfer and integration between various systems.
• Data Transformation: Perform data transformation activities, including data cleansing, data mining, and data processing, utilizing a variety of technologies and tools.
• Continuous Improvement: Collaborate with cross-functional teams to drive changes and enhancements based on data-driven findings.
• Data Mapping: Identify and present key performance indicators (KPIs) based on existing data points and datasets.