Senior Data Analyst
Citi · Chennai, Tamil Nadu, India
- On site
- Full-time
- $120,000 / year
- Chennai, Tamil Nadu, India
Job highlights
- Develop Python automation for data quality.
- Analyze data for quality issues and insights.
- Utilize Pandas, NumPy, PySpark for data.
- Enhance ETL processes and data integration.
- Collaborate with cross-functional teams.
About the role
About Citi
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We have 200+ years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities.
About AIM
Analytics and Information Management (AIM) is a global community that is driving data driven transformation across Citi in multiple functions with the objective to create actionable intelligence for our business leaders. We are a fast-growing organization working with Citi businesses and functions across the world.
Job Description
We are seeking a highly skilled, detail-oriented, and motivated Python SME (Automation Developer) to join our team. The ideal candidate will be responsible for designing, developing, and maintaining data quality automation solutions using Python. This role requires a deep understanding of data quality principles, proficiency in Python, and experience with data processing and analysis.
Key Responsibilities
- Design, develop, and implement data quality automation processes and solutions to identify, measure, and improve data quality.
- Conduct strategic data analysis, identify insights and implications, and make strategic recommendations.
- Develop data displays that clearly communicate complex analysis.
- Write and optimize Python scripts and applications to support data quality initiatives.
- Use Python libraries such as Pandas, NumPy, and PySpark for data manipulation and processing.
- Develop and enhance ETL processes to ensure accurate and timely data integration and transformation.
- Analyze data sets to identify data quality issues, trends, and anomalies, providing insights and recommendations for improvement.
- Support manual DQ efforts as required.
- Develop and execute test plans to validate the effectiveness of data quality solutions.
- Maintain comprehensive documentation of data quality processes, procedures, and standards.
- Work closely with data analysts, data engineers, DQ testers, and other team members and stakeholders to understand data requirements and deliver high-quality data solutions.
Required Skills
- Proficiency in Python and related libraries (Pandas, NumPy, PySpark, pyTest).
- Experience with data quality tools and frameworks.
- Strong understanding of ETL processes and data integration.
- Knowledge in SQL is an added advantage.
- Familiarity with data governance and data management principles.
- Excellent analytical and problem-solving skills with a keen attention to detail.
- Strong verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.
- Ability to work effectively both independently and as part of a team.
Qualifications
- Bachelor’s degree in computer science or information technology. Advanced degree is a plus.
- Minimum of 5+ years of relevant experience in machine learning, data quality automation, and Python Development.
- 1-2 years hands-on experience developing GenAI systems using frameworks similar to LangGraph or LangChain, etc.
- Proven experience with Python libraries for data processing and analysis.
- Ability to effectively use complex analytical, interpretive, and problem-solving techniques.
Key skills/competency
- Python
- Data Quality Automation
- Data Analysis
- ETL Processes
- Pandas
- NumPy
- PySpark
- SQL
- GenAI Systems
- Data Governance
Skills & topics
- Senior Data Analyst
- Python
- Data Quality
- Automation
- ETL
- Pandas
- NumPy
- PySpark
- GenAI
- Data Governance
- Machine Learning
- Data Management
- SQL
- Developer
- Financial Services
How to get hired
- Tailor your resume: Highlight Python, data quality, ETL, Pandas, NumPy, PySpark, and GenAI experience. Quantify achievements.
- Craft a strong cover letter: Emphasize your problem-solving skills and passion for data quality at Citi.
- Prepare for technical interviews: Brush up on Python coding, data structures, algorithms, SQL, and data quality concepts.
- Demonstrate GenAI familiarity: Be ready to discuss your experience with LangChain or similar frameworks.
- Research Citi's values: Understand their mission and how your skills align with their goals.
Technical preparation
Master Python, Pandas, NumPy, PySpark.,Practice SQL queries and data manipulation.,Review data quality frameworks and ETL concepts.,Understand GenAI concepts and libraries.
Behavioral questions
Describe a complex data problem solved.,How do you ensure data accuracy?,Explain technical concepts to non-technical people.,How do you manage team collaboration?
Frequently asked questions
- What specific Python libraries are most important for this Senior Data Analyst role at Citi?
- For this Senior Data Analyst position at Citi, proficiency in Python libraries such as Pandas, NumPy, and PySpark is crucial for data manipulation, processing, and analysis. Experience with pyTest for testing is also highly valued.
- What kind of experience is needed with GenAI systems for this role?
- The role requires 1-2 years of hands-on experience developing GenAI systems using frameworks like LangGraph or LangChain. This indicates a need for understanding and applying newer AI technologies within data automation.
- Beyond Python, what other technical skills are beneficial for this position at Citi?
- While Python is central, knowledge of SQL is a significant advantage. Familiarity with data quality tools, ETL processes, data governance, and data management principles will also strengthen your application for this role.
- What are the key responsibilities of a Senior Data Analyst focused on automation at Citi?
- Key responsibilities include designing and implementing data quality automation solutions using Python, conducting strategic data analysis, developing ETL processes, identifying data quality issues, and collaborating with various teams to deliver high-quality data solutions.
- What qualifications are necessary to be considered for the Senior Data Analyst position at Citi?
- A Bachelor's degree in computer science or information technology is required. You'll also need a minimum of 5+ years of relevant experience in machine learning, data quality automation, and Python development.
- How important is experience with data quality tools and frameworks for this role?
- Experience with data quality tools and frameworks is explicitly listed as a required skill. Demonstrating familiarity and practical application of these will be important for success in this role.
- What kind of analytical and problem-solving skills are expected?
- Excellent analytical and problem-solving skills with a keen attention to detail are essential. The ability to use complex analytical, interpretive, and problem-solving techniques is also a key requirement.
- How does this role contribute to Citi's mission?
- This role contributes to Citi's mission by ensuring data integrity and enabling data-driven transformation within the Analytics and Information Management (AIM) group. High-quality data supports better business decisions, which in turn enables growth and economic progress for clients.