Working knowledge of SAP products (Datasphere, SAC, S/4HANA, Success Factors, Workforce, etc.)
Ability to communicate effectively both orally and in writing.
Proficiency in developing/ documenting data architecture, coding, machine learning, and ETL/ETL processes.
Be well-versed in database tools and data warehouse solutions.
Self-starter thrives in ambiguity and has an investigator mindset of wanting to get to the bottom of problems.
Strong problem-solving and critical thinking abilities, with a keen attention to detail.
An agile, growth-minded approach, demonstrated through a history of driving projects from ideation to impact.
Ability to use advanced tools such as Power BI, Excel, Python, R, Tableau, etc.
Ability to implement data quality checks and validation procedures to ensure the accuracy and reliability of the data used for analytics.
Skilled in using data warehousing tools, data integration tools, and data transformation languages like SQL and potentially Python or R.
Skilled at working closely with data analysts and data scientists to understand their analytical requirements and tailor data pipelines accordingly.
Skills in designing data models using techniques like normalization, denormalization, and dimensional modeling.
Ability in building and maintaining the infrastructure and tools needed for data analysis.
Transforming raw data into a format that's accessible and usable for analysts and other stakeholders
Maintaining data documentation
Technical prowess in programming, database management, and cloud computing platforms
Knowledge of how data can be used for statistical analysis and modeling
