Analyst - Data Engineering

Nuveen; Mumbai; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

TIAA in Mumbai/Pune is seeking a Data Engineering Analyst to join the Marketing & Communications Data Engineering team. You will build and optimize large-scale data pipelines enabling marketing analytics, campaign measurement, brand tracking, and customer insights.

The role emphasizes data quality, governance, and collaboration with marketing technology, analytics, and business teams to translate requirements into scalable solutions.

Qualifications

• Strong hands-on experience with Python and SQL for data extraction, transformation, and validation.
• Experience with Snowflake or similar cloud-based data platforms (AWS, etc.).
• Understanding of data quality concepts and ETL/ELT processes.
• Familiarity with marketing data platforms like Google Analytics, SFMC, or CRM data.

Responsibilities

• Build, maintain, and optimize data pipelines that support marketing analytics, campaign performance measurement, brand tracking, and customer segmentation.
• Collect, process, and deliver large-scale marketing and customer data to the user community with accuracy and timeliness.
• Resolve systemic data errors, monitor the marketing data ecosystem, and scale data solutions.
• Implement and monitor automated data quality controls to maintain data integrity.
• Identify syntax, structure, and semantics for each marketing data source and document findings for stakeholders.
• Support cyclical production releases with up-to-date documentation and communicate data issues to stakeholders.

Skills

Python

SQL

Snowflake

AWS

Education

Bachelor's degree in a relevant field

Tools

Google Analytics

SFMC

CRM data platforms

Job description

## Analyst - Data EngineeringApply: Hybrid Flex: Mumbai, India: Pune, IND: Full time: Posted Today: End Date: October 30, 2026 (30+ days left to apply): R260500232We 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** 5ICKey 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 SkillsApplication 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