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Pune · On-site · Oct 13
Investment & Asset Management · 10000+ Employees · New York, US
Every worker deserves a secure retirement. For more than 100 years, weʼve delivered it for millions of people—and weʼre not done yet. Founded to help educators retire with dignity, today weʼre a market-leading retirement company fueled by world-class asset management. But weʼre not just another legacy financial services firm. Weʼre fighting harder than ever before for our clients and the many Americans who need us. And weʼre hiring. When you work at TIAA, youʼre making a difference in the lives of our clients. Weʼre always on the lookout for great people to become part of our coalition of champions—join our diverse and inclusive team today in the fight to help more people to and through retirement.
Hiring: Engineering
What employees say
+ Great work life balance. Good company for retirement
− Less package compared to competitors. Less growth in projects and technologies.
More reviews on the company profile.
Interview experience · Recruitment Coordinator
The interview process was Very smooth, hassle-free with quick updates and an openly communicated interview. There are 2 rounds of interviews and both are majorly done virtually. Also the team is very nice in terms of the
Average difficulty · Mumbai · 305 reports
More interview insightsJob description
Overview
We are seeking a detail-oriented and technically strong Data Engineering Analyst to join TIAA's Marketing & Communications Data Engineering team.
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.
- 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.
Qualifications
- No Experience Required
- 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.
Nice to have
- 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.
Education
- University (Degree) Preferred
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Job application FAQ
Last updated 19 October 2026
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- Is Analyst - Data Engineering remote or on-site in Pune, Maharashtra (+1 other)?
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