SAP Data - SAP Datasphere and SAC Consultant - Fixed term

EY

Bengaluru

On-site

INR 1,500,000 - 2,100,000

Full time

14 days+

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Job summary

EY in Bengaluru seeks a SAP Data - SAP Datasphere and SAC Consultant to design and implement data pipelines, models, and dashboards. The candidate will harmonize data from SAP and non-SAP sources, build analytics-ready layers, and deliver actionable insights for Finance, Accounting, and Commercial teams.

The role involves forecasting, anomaly detection, and presenting findings clearly to business leaders, with a focus on data quality, governance, and end-to-end ownership.

Qualifications

  • Experience building data pipelines and SAP Datasphere models.
  • Dashboard development in SAP Analytics Cloud (SAC) for finance and commercial stakeholders.
  • Strong SQL for data extraction, transformation, and analysis.
  • Proficiency in Python for data wrangling, EDA, and modeling.
  • Experience pulling data from diverse systems and APIs into analytics workflows.

Responsibilities

  • Design, build, and maintain data pipelines and models in SAP Datasphere.
  • Ingest and harmonize data from SAP and non-SAP sources into analytics-ready layers.
  • Develop dashboards and stories in SAC for stakeholders, with KPIs and drill-downs.
  • Conduct EDA and RCA to translate findings into business insights.
  • Build forecasting models using SAP data and validate model quality.
  • Collaborate with Finance, Accounting, and Commercial teams to prioritize deliverables.

Skills

SAP Datasphere
SAP Analytics Cloud
SQL
Python
Data integration
Data cleaning

Education

BE or Equivalent

Tools

REST APIs

Job description

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, 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.
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/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.

Education Qualificaiton : BE Or Equlant

Job Title

SAP Data - SAP Datasphere and SAC Consultant

Roles & Responsibilities

Must be willing to work in shift: 9:30 AM to 06:30 PM (all hours in IST), if there is any Emergency Support, he should be willing to extend and Provide Required Support.

Data Engineering & Pipelines
  • Design, build, and maintain data pipelines and models in SAP Datasphere (spaces, views, data flows, replication, and integration with source systems).
  • Ingest and harmonize data from SAP source systems (e.g. S/4HANA, ECC, BW/4HANA) and non-SAP sources into curated, analytics-ready layers.
  • Implement data cleansing, transformation, and validation logic to ensure accuracy, completeness, and consistency.
  • Optimize models and queries for performance and cost, applying good practices for semantic layers and reusable views.
Dashboards & Visualization
  • Build, publish, and maintain interactive dashboards and stories in SAP Analytics Cloud (SAC) for Finance, Accounting, and Commercial stakeholders.
  • Design clear, decision-oriented visualizations with well-defined KPIs, drill-downs, and self-service capabilities.
  • Manage data connections (live and import), models, and access within SAC.
Analysis, Insight & Root‑Cause
  • Perform Exploratory Data Analysis (EDA) to understand data quality, distributions, trends, and relationships.
  • Conduct Root-Cause Analysis (RCA) on financial and commercial variances, anomalies, and performance issues.
  • Translate analysis into actionable insights and recommendations communicated in plain business language to non-technical stakeholders.
Modeling & Advanced Analytics
  • Build forecasting models on SAP data (e.g. revenue, cost, cash, demand, working capital) using appropriate statistical or ML techniques.
  • Develop anomaly detection to flag unusual transactions, postings, or patterns in SAP data for review by Finance / Controls.
  • Apply appropriate ML methods to prediction, segmentation, and pattern-detection problems, and validate model quality.
Collaboration & Ownership
  • Partner with Finance, Accounting, and Commercial teams to gather requirements and prioritize deliverables.
  • Document pipelines, models, and dashboards; ensure reproducibility and maintainability.
  • Champion data quality and governance across the analytics stack.
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