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CDP Data Engineer

4 weeks ago

Bengaluru, India Thomson Reuters Full time

Summary:

Are you passionate about transforming raw data into actionable insights? Do you thrive on integrating diverse data sources and building robust data models, pipelines, and platforms that empower businesses to leverage customer data for audience segmentation and activation? Reuters Data & Analytics team is seeking a talented CDP Data Engineer to deliver high-quality data engineering solutions in support of business intelligence, data science, and self-service analytics.

About the Role:

As a CDP Data Engineer, you will:

Collaborate closely with business and data teams to gather requirements and translate them into effective data engineering solutions.

Implement data cleansing, enrichment, and transformation processes to ensure the availability of high-quality data for analytics, modeling, and business activation.

Configure and manage seamless integration of the CDP with various data sources and activation destinations, including CRM, marketing automation, and analytics platforms.

Design and execute testing plans, develop data quality checks, validation rules, and monitoring mechanisms to uphold data accuracy and integrity within the CDP.

Monitor data pipeline performance, resolve issues promptly, and proactively identify opportunities for improvement.

Explore and analyze large volumes of data with curiosity and rigor.

Troubleshoot and resolve technical challenges efficiently.

Stay current with, and be open to learning, emerging technologies in data engineering, data science, and cloud computing.

About You:

You are an ideal candidate for the CDP Data Engineer role if you have:

5+ years of experience in data engineering or analytics domains.

Bachelors degree in Computer Science, Information Technology, Engineering, Statistics, Mathematics, Data Science, or a related field.

Proficiency in SQL and data manipulation.

Strong programming skills in languages such as Python.

Experience working on Customer Data Platform (CDP) implementations is a plus.

Strong data modeling skills, including knowledge of various schemas such as snowflake and star.

Solid knowledge of building ETL workflows, database design, and query optimization.

Hands-on experience with data pipeline and transformation tools such as dbt, Glue, FiveTran, Alteryx, or similar.

Experience with cloud-based data warehouse solutions such as Snowflake, Redshift, or Azure.

Familiarity with orchestration tools like Airflow or Dagster.

Understanding of data privacy, compliance regulations, and industry best practices.

Excellent problem-solving abilities and a proactive approach to technical issues.

Strong communication skills, with the ability to collaborate effectively with both technical and non-technical team members across geographies.