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REQUIREMENT_ID_1340 β€’ 3-DAY_ACTIVE_POLICY

Analyst – Data Engineering

Company
Company TIAA
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 8 LPA - 12 LPA
Location
Location Mumbai, Maharashtra; Pune, Maharashtra
Posted Date
Posted Date Yesterday
Python SQL ETL/ELT Data Pipelines Snowflake AWS Data Quality API Integration Data Validation Analytical Skills Problem Solving Communication
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Aptitude and Logical Reasoning Practice Open Resource β†—
Enhances problem‑solving skills essential for data engineering interviews.
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Interview Preparation for Technical Roles Open Resource β†—
Provides insights into common technical interview questions and best practices.
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Coding Practice and Project Building Open Resource β†—
Helps build coding projects and improve programming proficiency.
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Algorithmic Challenges and Data Structures Open Resource β†—
Strengthens algorithmic thinking and data structure knowledge for coding interviews.

Bachelor’s degree in Computer Science, Information Technology, Engineering, or related fields. No specific branch or percentage requirement mentioned; however, a minimum of 60% or 6.5 CGPA is typically expected for entry-level roles. No backlog policy is specified, but maintaining a clean academic record is advisable.

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Round 1: Technical interview – Python & SQL fundamentals
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Round 2: Technical interview – Data pipelines, Snowflake, ETL/ELT concepts
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Round 3: HR interview
TIAA, a leading global financial services organization, is expanding its Marketing & Communications Data Engineering team in India. With a legacy of serving clients across retirement, investment, and insurance domains, TIAA brings a culture of innovation, data-driven decision making, and a commitment to employee growth. The company’s Indian operations focus on delivering high-impact solutions that empower marketing teams to measure campaign performance, understand customer journeys, and drive brand insights. The Analyst – Data Engineering role is designed for freshers who are eager to dive into the world of data engineering. You will work closely with marketing technology, analytics, and business stakeholders to build and maintain robust data pipelines that feed into reporting and analytics platforms. Your responsibilities will include designing ETL/ELT processes, ensuring data quality, automating data validation checks, and supporting data governance initiatives. Key responsibilities: 1. Build and maintain scalable data pipelines using Python and SQL. 2. Extract, transform, and load data from diverse sources such as APIs, CRM systems, and analytics platforms. 3. Implement automated data quality checks and resolve data issues. 4. Collaborate with stakeholders to understand data requirements and translate them into technical solutions. 5. Document data models, pipeline logic, and metadata for future reference. 6. Monitor pipeline performance and troubleshoot failures. 7. Support the creation of semantic data layers for marketing analytics. 8. Participate in data governance and compliance discussions. 9. Stay updated on cloud data platform advancements (Snowflake, AWS). 10. Contribute to continuous improvement of data engineering practices. Tech stack: Python, SQL, Snowflake (or similar cloud-based platforms), AWS services, ETL/ELT tools, API integration, data validation frameworks. Growth path: Starting as an Analyst, you can progress to Senior Data Engineer, Lead Data Engineer, or Data Engineering Manager, with opportunities to specialize in cloud architecture, data governance, or advanced analytics. Why join TIAA? The organization offers a collaborative environment, exposure to cutting-edge cloud technologies, and a focus on professional development. Employees benefit from comprehensive health and wellness programs, flexible work arrangements, and a culture that values work-life balance while encouraging innovation and career advancement. This role is an excellent launchpad for aspiring data engineers, providing hands‑on experience with real-world marketing data, exposure to enterprise cloud platforms, and mentorship from seasoned professionals.

TIAA β€” QA & Automation Testing Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
TIAA Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for TIAA and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Python, SQL, ETL/ELT, Data Pipelines, Snowflake, AWS, Data Quality, API Integration, Data Validation, Analytical Skills, Problem Solving, Communication) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
TIAA Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between Implicit Wait, Explicit Wait, and Fluent Wait in Selenium? Answer β–Ό
Model Answer: Implicit Wait sets a global timeout for all element lookups. Explicit Wait pauses execution until a specific ExpectedCondition (e.g. elementToBeClickable) is met. Fluent Wait allows defining polling frequency and ignoring specific exceptions like NoSuchElementException.
Explain the Page Object Model (POM) and its advantages in Test Automation. Answer β–Ό
Model Answer: POM is a design pattern that creates an object repository for web UI elements. It separates test scripts from page locators, reducing code duplication and making maintenance easy when UI elements change.
How do you handle dynamic WebElements whose ID changes on page reload? Answer β–Ό
Model Answer: Use dynamic XPath methods like contains(), starts-with(), text(), or XPath axes (ancestor, following-sibling, parent) instead of brittle absolute paths.
What is the difference between @BeforeMethod and @BeforeClass in TestNG? Answer β–Ό
Model Answer: @BeforeClass runs once before the first test method in the current class, while @BeforeMethod executes before each individual test method.
How do you validate REST API response codes and JSON payload using Postman / RestAssured? Answer β–Ό
Model Answer: In RestAssured: given().when().get('/endpoint').then().assertThat().statusCode(200).body('status', equalTo('ACTIVE')).
Why do you want to join TIAA as a Analyst – Data Engineering?
Preparation Tip: Highlight TIAA's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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