Senior SAP SAC Consultant (32 LPA, SAP Datasphere and SAP Analytics Cloud)

Job DescriptionRole: Senior SAP SAC Consultant (SAP Datasphere and SAP Analytics Cloud) Location: Bangalore (Hybrid) Job Type: Permanent Mandatory Skills SAP Datasphere and SAP Analytics Cloud Job Description 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, NumPy, scikit-learn, statsmodels). 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. YouTube 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. Preferred / Nice-to-Have · Experience with S/4HANA and/or BW/4HANA 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.

BigQuery, 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.