Analyst - Data Engineering

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.

Key Responsibilities And Duties

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.

Educational Requirements

University (Degree) Preferred

Work Experience

No Experience Required

Career Level

5IC

Key Responsibilities And Duties:

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.

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.

Related Skills

Application Programming Interface (API) Development/Integration, Automation, Communication, Consultative Communication, Containerization, DevOps, Enterprise Application Integration, Influence, Organizational Savviness, Problem Solving, Prototyping, Relationship Management, Scalability/Reliability, Software Development Life Cycle, Systems Design/Analysis

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Company Overview

TIAA Global Capabilities was established in 2016 with a mission to tap into a vast pool of talent, reduce risk by insourcing key platforms and processes, as well as contribute to innovation with a focus on enhancing our technology stack. TIAA Global Capabilities is focused on building a scalable and sustainable organization , with a focus on technology , operations and expanding into the shared services business space.

Working closely with our U.S. colleagues and other partners, our goal is to reduce risk, improve the efficiency of our technology and processes and develop innovative ideas to increase throughput and productivity.