Skills:
Data Analysis, SQL, Statistical Analysis, Data Visualization, Python, Problem Solving, ETL,
Role: Data Analyst
Engagement type: Contract
Working Hours: Flexible - Working with Mandatory PST overlap from 10 PM to 12 AM (IST)
Required
- Bachelors degree in Computer Science, Information Systems, Statistics, or a related field.
- 8+ years of experience in data analysis or data warehousing.
- Proficiency in SQL for data extraction and manipulation.
- Experience with data warehousing tools and technologies (e.g., Snowflake, MS Fabric, etc.).
- Knowledge of ETL tools (e.g. WhereScape, Informatica, Talend, or Alteryx).
- Strong analytical and problem-solving skills.
- Experience with BI tools (e.g., Tableau, Power BI, Looker).
- Familiarity with programming languages like Python, etc..
- Excellent communication and teamwork skills.Desired
- Familiarity with at least one public cloud provider (AWS, Azure, or GCP) and their respective data & analytics products and platforms
- Understanding of data governance, security, and compliance best practices.
Key Responsibilities
- Data Quality Assurance:
- Develop and implement data quality processes to ensure accurate and consistent data.
- Perform data profiling and validation to identify and resolve data anomalies and inconsistencies.
- Data Warehouse Development:
- Collaborate with stakeholders to understand data requirements for the finance domain.
- Support the development and testing of Data Vault 2.0-based models.
- ETL Process Validation:
- Test and validate ETL processes built using automation tools such as WhereScape RED (or any ETL tool).
- Ensure data integrity during data extraction, transformation, and loading operations.
- Collaboration & Documentation:
- Work closely with data modelers, ETL developers, and business analysts to align on data requirements.
- Document data quality issues, test cases, and resolutions comprehensively.
- Automation & Tool Utilization:
- Explore opportunities for automating data quality checks and validations.
- Continuous Improvement:
- Analyze recurring data issues and recommend solutions for system improvements.
- Stay updated with best practices in data quality engineering and apply them to the project.
- Experienced in ETL Test Automation tools like QyerySurge, Big EVAL, Etc.