Data Engineer

• Help define company data assets (data model), spark, sparkSQL and hiveSQL jobs to populate data models
• Collaborate with cross-functional teams, including Marketing, Data Science, and IT, to understand data requirements and design efficient data pipelines for marketing data integration.
• Develop, maintain, and optimize ETL processes to extract, transform, and load data from various sources, including marketing platforms, CRM systems, web analytics, and third-party APIs.
• Build and maintain robust data architectures that support data warehousing, reporting, and analytics for marketing initiatives.
• Ensure data accuracy, consistency, and quality through rigorous data validation and cleansing procedures.
• Troubleshoot and resolve data-related issues, including data transformation errors, pipeline failures, and data synchronization problems.
• Stay current with the latest trends and advancements in marketing technologies, data engineering, and SQL to continuously improve data processes and capabilities.
• Work closely with Data Scientists to provide them with access to clean, relevant, and accurate data for their analyses and modeling efforts.
• Collaborate on the design and implementation of data governance and data security policies to protect sensitive marketing data.
• Participate in code reviews, documentation, and knowledge sharing to maintain high standards of code quality and team collaboration.

• Bachelor's degree in computer science, Information Technology, or related field. Master's degree preferred.
• Proven experience (5+ years) as a Data Engineer, with a significant focus on marketing technologies and data integration.
• Proficiency in SQL, Aqueduct, Airflow DAGs with a strong ability to write complex queries, optimize query performance, and work with large datasets.
• Experience with Customer Data Platforms (CDP) like Segment, mParticle, Tealium AudienceStream or other industry leading CDP technology would be a plus
• Hands-on experience with marketing platforms such as Google Analytics, Adobe Analytics, Marketo, HubSpot, Salesforce Marketing Cloud, etc would be a plus
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud, and their data services (S3, Redshift, BigQuery, etc.).
• Strong programming skills in languages such as Python or Java for data processing and scripting tasks.
• Excellent problem-solving skills, attention to detail, and the ability to troubleshoot complex data issues.
• Solid understanding of data warehousing concepts, data modeling, and database design principles.
• Knowledge of data governance, data security, and compliance practices within a marketing context.
• Effective communication skills to collaborate with technical and non-technical stakeholders.
• Experience with version control systems (e.g., Git) and Agile development methodologies.

Last updated on Aug 23, 2023