Identifying and gathering data from various sources.
Ensuring data accuracy and completeness.
Developing processes for data ingestion and transformation.
Data Processing and Storage: Cleaning, transforming, and validating data.
Implementing data storage solutions (databases, cloud storage, etc.).
May be involved in data security and access control.
Data Analysis and Insights:
Performing data analysis to identify trends and patterns.
Developing data models and reports.
Communicating findings to stakeholders.
Data Archival and Deletion:
Developing and implementing data archiving policies.
Ensuring data retention and deletion according to regulations and business needs.
Documentation and Training: Documenting data processes and procedures.
Policy, procedure, and exception technical writing
Providing training to users on data access and usage.
Skills and Qualifications: Technical Skills: Must be proficient in client Enterprise Data Governance policies, standards, procedures Proficiency in programming languages (e.g., Python, SQL) is helpful.
Experience with databases and data warehousing technologies.
Knowledge of data modelling and data analysis techniques.
Familiarity with data security and privacy regulations.
Soft Skills:
Strong analytical and problem-solving skills.
Excellent communication and interpersonal skills.
Ability to work independently and as part of a team.
Attention to detail and a commitment to data quality.
Under direct supervision of Sr. Data Analysts, organizes ,schedules meetings with key business stakeholders to understand underlying problem statement and synthesize corrective user action
Provides deep-dive analysis into business problems and provide actionable insights for the respective teams
Participates in presentation of reports to key internal or external stakeholders, communicating the key findings
Builds ad-hoc and standard reports and dashboards to drive consistent data-driven insights
Identifies problem statements and creates supplementing data to support problem root cause
Should have proven experience in database design, data-modelling, SQL server etc.
Has prior experience in building statistical models. Usually works with reactive statistical models i.e., develop insights based on historical data such as high performing products in the existing sales mix
Proficient with productivity tools such as MS Word, PowerPoint, Excel etc. Understanding on any of the BI tools such as SAS, Tableau, Cognos, etc.