Senior Developer - SAP S4HANA, Java, SAP PLM
HCLTech
Bangalore, Karnataka, IndiaPosted 21 days agoDiscoveredMatch locked
Full-time
Mandatory Skills
SAP Datasphere and SAP Analytics Cloud
Skill to Evaluate
SAP Datasphere and SAP Analytics Cloud
Experience
4 to 6 Years
Location
Bengaluru
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.
Key Responsibilities
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.
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.
Other Requirements
null
Not included in the source posting: about the role, benefits.
Skills
sappythonmysqlnumpypandaspostgresqlrest-apisqlbigquerydatabricksgitmachine-learning
Who can apply
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