Analyst – Data Engineering

TIAA is looking for a detail-oriented Data Engineering Analyst to support marketing analytics, campaign measurement, brand research, and customer insights. The role focuses on building and maintaining scalable data pipelines and making sure data is accurate, reliable, and useful for business teams. Responsibilities

• Build, maintain, and optimize data pipelines for marketing analytics, campaign performance, brand tracking, and customer segmentation.
• Collect, process, and deliver large datasets accurately and on time.
• Identify and resolve data errors and monitor data systems.
• Implement automated data-quality checks.
• Understand the structure and meaning of data from different sources and document it.
• Maintain release documentation and communicate known data issues.
• Support data governance and stewardship.
• Work with marketing technology, analytics, and business teams to translate requirements into scalable solutions.
• Help curate clean datasets and metadata for semantic data layers and responsible AI use.

Required skills

Hands-on Python and SQL for data extraction, transformation, and validation. Snowflake or a similar cloud-based data platform, such as AWS. Understanding of data quality, API/file-transfer pipelines, and ETL/ELT processes. Analytical thinking, problem-solving, and attention to detail. Communication skills for working with technical and business stakeholders. Preferred skills Marketing analytics platforms such as Google Analytics or SFMC. CRM and marketing data ecosystems. Data governance tools and practices. Experience with large and complex datasets. Basic AI/ML data preparation, semantic data layers, or RAG concepts. Exposure to responsible AI, AI governance, feature stores, vector databases, or dbt.