Data Engineer
Thomson Reuters Bengaluru, Karnataka, India
Job Description
"Unlock the power of data engineering at Thomson Reuters, where innovative AI solutions and cutting-edge technologies drive business growth and inform strategic decision-making."
As a Data Engineer at Thomson Reuters, you will play a pivotal role in shaping the future of data-driven insights and solutions. With a strong foundation in AI, machine learning, and data engineering, you will design, develop, and maintain complex reports, dashboards, and data pipelines that drive business growth and inform strategic decision-making.
In this role, you will work closely with stakeholders to define complex reporting needs, deliver high-impact actionable insights, and drive data-informed strategies. You will leverage cutting-edge technologies such as dbt, Snowflake, Power BI, Tableau, Excel, and PowerPoint to create scalable and dynamic solutions.
Why you should learn this:
The demand for data engineers with AI expertise is high, with a projected growth rate of 14% annually, outpacing the overall job market.
Expected Salary: $120,000 - $180,000 per year, depending on experience and qualifications.
How it works:
- Design and develop complex reports, dashboards, and data pipelines using AI platforms, dbt, Snowflake, Power BI, Tableau, Excel, and PowerPoint.
- Implement AI across various solutions, leveraging enterprise AI platforms, tools, LLMs, RAGs, etc.
- Develop and build scalable LLM/RAG-based solutions, data pipelines, ETL workflows, and optimize data models.
Core Concepts to Master
AI Platform Architecture
Design and implement scalable AI platform architectures that integrate multiple tools and technologies, such as dbt, Snowflake, Power BI, Tableau, Excel, and PowerPoint.
Machine Learning Techniques
Apply machine learning techniques, such as predictive modeling, natural language processing, and computer vision, to innovate solutions and provide predictive insights.
Data Engineering Best Practices
Follow data engineering best practices, such as data modeling, data warehousing, and data governance, to ensure data quality, security, and integrity.
Cloud-Based Data Solutions
Design and implement cloud-based data solutions, such as Snowflake, AWS Lake Formation, and Azure Synapse Analytics, to support scalable and on-demand data processing.
Interview Questions (Beginner)
- What do you know about AI platforms, such as dbt, Snowflake, Power BI, Tableau, Excel, and PowerPoint?
- Can you explain the concept of machine learning and its applications in data engineering?
- How do you ensure data quality, security, and integrity in data engineering?
Job Overview
Advance Questions
- • Design a scalable AI platform architecture that integrates multiple tools and technologies.
- • Implement a machine learning model to predict customer churn using a dataset.
- • Explain the concept of data warehousing and its importance in data engineering.