Data Engineer

Must have skills: Snowflake, Python and SQL.

Key Responsibilities:

• Implement data solutions across Marketing, Sales, and Customer Service, using technologies such as DBT, Snowflake, and Azure.

• Design and optimize data pipelines that integrate various data sources (1st party, 3rd party, operational) to support business intelligence and advanced analytics.

• Develop data models and data flows that enable personalized customer experiences and support omnichannel marketing and customer engagement.

• Lead efforts to ensure data governance, data quality, and data security, adhering to compliance with regulations such as GDPR and CCPA.

• Implement and maintain data warehousing solutions in Snowflake to handle large-scale data processing and analytics needs.

• Optimize workflows using DBT to streamline data transformation and modeling processes.

• Leverage Azure for cloud infrastructure, data storage, and real-time data analytics, while ensuring the architecture supports scalability and performance.

• Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to ensure data architectures meet business needs.

• Support both real-time and batch data integration, ensuring data is accessible for actionable insights and decision-making.

• Continuously assess and integrate new data technologies and methodologies to enhance the organization's data capabilities.

Qualifications:

• 7+ years of experience in Data Engineering, with specific expertise in DBT, Snowflake, and Azure.

• Strong understanding of data modeling, ETL/ELT processes, and modern data architecture frameworks.
• Experience designing scalable data architectures for personalization and customer analytics across marketing, sales, and customer service domains.

• Expertise with cloud data platforms (Azure preferred) and Big Data technologies for large-scale data processing.

• Hands-on experience with Python for data engineering tasks and scripting.

• Proven track record of building and managing data pipelines and data warehousing solutions using Snowflake.

• Familiarity with Customer Data Platforms (CDP), Master Data Management (MDM), and Customer 360 architectures.

• Strong problem-solving skills and ability to work with cross-functional teams to translate business requirements into scalable data solutions.

• Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's degree preferred.

Preferred:

• Experience working with AI/ML models for customer analytics and personalization.

• Knowledge of data privacy and compliance regulations (GDPR, CCPA).