Job Summary
We are seeking a detail-oriented and technically strong Data Engineering Analyst to join TIAA's Marketing & Communications Data Engineering team. This role is responsible for implementing large-scale, complex data projects that support marketing analytics, campaign measurement, brand research, and customer insights initiatives. The analyst will work closely with marketing technology, analytics, and business stakeholders to ensure high-quality data is accessible, reliable, and actionable. Working under direct supervision, this contributes to building and maintaining scalable data pipelines that power TIAA's marketing and communications strategies.
Responsibilities
- Build, maintain, and optimize data pipelines that support marketing analytics, campaign performance measurement, brand tracking, and customer segmentation initiatives.
- Collect, process, and deliver large-scale marketing and customer data to the user community, ensuring accuracy, completeness, and timeliness.
- Resolve systemic data errors, monitor the marketing data ecosystem, and develop strategies to scale data solutions.
- Implement and monitor automated data quality controls to maintain data integrity across marketing data platforms.
- Identify syntax, structure, and semantics for each marketing data source and document findings for stakeholder use.
- Manage cyclical production releases by maintaining accurate and up-to-date documentation and communicating known data issues to marketing and analytics stakeholders.
- Support data governance and stewardship initiatives in alignment with TIAA's enterprise data strategy.
- Collaborate with marketing technology, analytics, and business teams to understand data requirements and translate them into scalable data engineering solutions.
- Assist in curating clean, consistently defined datasets and metadata that can support semantic data layers and responsible AI consumption.
Educational Requirements
- University (Degree) Preferred
Work Experience
Career Level
5IC
Required Skills
- Strong hands-on experience with Python, and SQL for data extraction, transformation, and validation.
- Experience working with Snowflake or similar cloud-based data platforms like AWS etc.
- Understanding of data quality concepts, API/File Transfer based data pipelines, and ETL/ELT processes.
- Familiarity with marketing data platforms like Google Analytics, SFMC, or CRM data is a plus.
- Strong analytical and problem-solving skills with keen attention to detail.
- Good communication skills to interact with both technical and business stakeholders across marketing and technology functions.
Preferred Skills
- Experience with Python for data automation, transformation, or validation tasks.
- Exposure to marketing analytics platforms or marketing data ecosystems.
- Familiarity with data governance tools and practices.
- Experience working with large and complex datasets.
- Basic familiarity with AI/ML data preparation, semantic or logical data layers, or retrieval-augmented generation (RAG) concepts is a plus.
- Exposure to responsible AI, AI governance, feature stores, vector databases, or semantic-layer tooling such as dbt is a good to have.