Data Engineer | NDA

📋 Description

• Build scalable ETL/ELT pipelines for third-party and first-party data.
• Data quality & enrichment: apply transformation, normalization, enrichment rules.
• Collaborate with product managers, data architects, and content experts.
• Operationalize matching and entity resolution using AI/ML tools.
• Monitor and troubleshoot pipelines; build alerts, logs, and metrics.
• dbt development: build pipelines from raw data to semantic models.

🎯 Requirements

• 4–8 years in data engineering building production-grade pipelines.
• Tech stack: SQL, Python, dbt; Snowflake; Spark; Airflow; Azure Data Lake.
• Azure preferred or other major cloud platforms.
• Data modeling, version control, CI/CD, and data governance.
• Curiosity & ownership: proactive, detail-oriented, and ownership mindset.
• Team player; cross-functional collaboration.

🎁 Benefits

• Fast-growing, high-impact team at the intersection of two key projects.
• Contribute to building the highest quality business directory.
• Startup-style group redefining consulting with productization and data.
• Work with cutting-edge data tools, including AI/ML enrichment.