TIAA hiring a data analyst in pune location and provides hybrid work model with high salary package
Company Overview
TIAA GBS India 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 GBS India 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.
Job ID: R240200234
Job role : Data Analyst
Qualifications: BE/B.Tech or other technical degree
Batch: Every graduate can apply
Experience: Fresher
Job location : Pune , Maharashtra
Last Date: ASAP
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Attention : Read all criteria carefully and make changes in resume by adding relevent keywords so you will get the interview call otherwise you will loose opportunity.
Key Responsibilities and Duties
- They are responsible for design and development of data flows and Big Data Platform deployment and implementation.
- Incumbents usually require expert knowledge in Apache, Hadoop, NoSQL databases, Spark, Hive etc.
Educational Requirements
- University (Degree) Preferred
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Work Experience
- No Experience Required
Job Role
- Conduct comprehensive data profiling and analysis to understand data structures, relationships, and patterns.
- Identify anomalies and discrepancies in the data and propose solutions for resolution.Perform data quality assessments to ensure accuracy, completeness, and consistency of data across various sources.
- Develop data quality rules and validations.
- Collaborate with data stewards and business users to cleanse and standardize data as per established guidelines.
- Implement data cleansing processes to improve overall data quality.
- Create and maintain metadata documentation for datasets, ensuring data lineage and facilitating easy discovery of information.
- Contribute to the development of a comprehensive data dictionary.
- Experience working with Entity \Account Reference Data across asset classes including equities, fixed income and derivatives.
- Experience/expertise in the use of some/all: AWS Databrew, Power BI, SQL, Excel query/pivot
- Experience/expertise in the use of some/all: Eagle Pace, Golden Source, Oracle SQL Developer, SnowFlake, AWS Quicksight.
- Knowledge of market data sources, products and tools
- Ability to work relatively independently and in a team-oriented, collaborative environment.
- Prioritization and problem-solving skills.
- Very good communication skills, written and verbal.
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Releted skills
- Collaboration:
- Ability to effectively work with a diverse team, leveraging individual strengths towards common goals.
- Demonstrated capacity to communicate ideas, listen actively, and contribute constructively within group settings.
- Proven track record of fostering a positive team environment and resolving conflicts collaboratively.
- Continuous Improvement Mindset:
- Dedication to seeking out opportunities for optimization and enhancement in processes, workflows, and outcomes.
- Willingness to adapt to changing circumstances and embrace new methodologies or technologies to drive improvement.
- Proactive approach to personal and professional development, including seeking feedback and integrating lessons learned into future endeavors.
- Data-Driven Business Intelligence:
- Proficiency in gathering, analyzing, and interpreting data to inform strategic decision-making within a business context.
- Ability to identify key performance indicators (KPIs) and develop actionable insights from quantitative and qualitative data sources.
- Experience with tools and techniques for extracting, transforming, and loading (ETL) data for business intelligence purposes.
- Data Engineering/Analytics:
- Strong foundation in data management principles, including data warehousing, data modeling, and database administration.
- Expertise in programming languages commonly used in data engineering and analytics, such as Python, SQL, or R.
- Familiarity with big data technologies and platforms, such as Hadoop, Spark, or NoSQL databases.
- Data Visualization:
- Proficient in conveying complex data insights through visualizations that are clear, concise, and impactful.
- Mastery of data visualization tools and libraries, such as Tableau, Power BI, matplotlib, or ggplot2.
- Understanding of design principles and best practices for creating effective data visualizations that resonate with diverse audiences.
- Predictive Modeling:
- Ability to develop and deploy statistical models to forecast future trends or outcomes based on historical data.
- Experience with machine learning algorithms and techniques for regression, classification, and clustering.
- Aptitude for evaluating model performance, iterating on model designs, and refining predictions through continuous validation and testing.
- Problem Solving:
- Demonstrated proficiency in identifying, analyzing, and solving complex problems through systematic approaches.
- Capacity to break down complex issues into manageable components and develop innovative solutions.
- Strong critical thinking skills, including the ability to evaluate alternative solutions and make data-driven decisions.
- Programming:
- Proficiency in one or more programming languages commonly used in data science and analytics, such as Python, R, or Java.
- Experience with software development practices, including version control, testing, and debugging.
- Ability to write efficient, scalable code for data processing, analysis, and visualization tasks.
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