SAP Datasphere Consultant

Location: Vasanthanagar

Job Description

Technical

· Proven experience building data pipelines and models in  SAP Datasphere  (or SAP Data Warehouse Cloud / BW modeling).

· Hands-on dashboard development in  SAP Analytics Cloud (SAC)  — models, stories, and connections.

· Strong  SQL  for data extraction, transformation, and analysis.

· Proficiency in  Python  for data wrangling, EDA, and modeling (e.g. pandas, Num Py, scikit-learn, stats models).

· Experience using  Python to pull and integrate data from diverse systems and APIs  — e.g. relational databases (MySQL, PostgreSQL), REST APIs, and third-party sources (e.g. You Tube API) — into analytics workflows.

· Solid understanding of  SAP data structures and storage nuances  — key tables, master vs. transactional data, document flow, ledgers, and how SAP financial/commercial data is organized (e.g. FI/CO, SD, MM).

· Experience with  data cleaning  and building trustworthy, analytics-ready datasets.
Domain

· Working knowledge of  Finance, Accounting, and Commercial  concepts (e.g. P&L, balance sheet, cost centers, profit centers, GL, revenue, margin, pricing, AR/AP).

· Ability to connect data work to real financial and commercial outcomes.
Analytical & Modeling

· Demonstrated experience with  forecasting  and/or  anomaly detection  on business data.

· Comfort with the full analytics lifecycle: EDA → RCA → insight → recommendation.
Soft skills

· Strong communication skills; able to explain technical findings to Finance and business leaders.

· Self-starter who can own problems end to end with limited supervision.

Preferred / Nice-to-Have

· Experience with  S/4

HANA  and/or  BW/4

HANA  data models.

· Familiarity with SAP CDS views, HANA Calculation Views, or ABAP for data sourcing.

· Exposure to Git/version control, CI for analytics, or orchestration tools.

· Experience with cloud data platforms (e.g. Big Query, Snowflake, Databricks) and integration into the SAP landscape.

· Knowledge of ML Ops or model deployment for production forecasting/anomaly workflows.

· Relevant degree in Finance, Accounting, Data Science, Computer Science, Statistics, Engineering, or equivalent experience.