Role: Data Engineer – SAP Integration

Experience: 8+ Years

Work Mode: Remote

Availability: Immediate / Short Notice Preferred

Required Skills

Python

SQL

PySpark

Databricks

SAP Integration / SAP Data Extraction

CI/CD

DevOps

Cloud – AWS / Azure / GCP

Important Vendor Requirements

Candidate should have strong hands-on experience with SAP integration / SAP data extraction.

Candidate should have hands-on experience integrating SAP data with Databricks, Data Lake, Data Warehouse, or other cloud-based data platforms.

Databricks certification is optional/preferred, but not mandatory.

Job Description

We are looking for a self-motivated and experienced Data Engineer with SAP Integration experience who is passionate about building scalable data solutions. The candidate will be responsible for taking data through its complete lifecycle, including data extraction, integration, processing, pipeline development, data infrastructure, and creation of reliable data products.

The ideal candidate should have strong hands-on experience with Python, SQL, PySpark, Databricks, and SAP data integration, along with experience working in cloud and DevOps/CI/CD environments.

Core Responsibilities

Design, develop, and maintain robust data pipelines using SQL, Python, PySpark, and Databricks.

Integrate and ingest data from SAP systems into enterprise data platforms and data lakes.

Develop data extraction and transformation processes for SAP data.

Work with SAP data sources such as SAP S/4HANA, SAP ECC, SAP BW/BW4HANA, or other relevant SAP systems.

Understand business requirements and design data provisioning pipelines for Finance, reporting, analytics, and external reporting domains.

Monitor and optimize data pipeline and query performance.

Troubleshoot operational and data-quality issues across pipelines and SAP integrations.

Build scalable ETL/ELT processes for structured and unstructured data.





Work closely with Data Analysts, Data Scientists, SAP teams, business stakeholders, and other engineering teams.

Drive architectural plans for future data storage, reporting, analytics, and SAP-integrated data solutions.

Ensure high availability, reliability, and quality of data pipelines.

Implement and maintain CI/CD pipelines for data engineering solutions.

Work in a DevOps environment and follow best practices for deployment, monitoring, and version control.

Required Qualifications

8–15 years of experience in Data Engineering / Software Engineering.

Strong hands-on experience with Python, SQL, PySpark, and Databricks.

3+ years of experience working with big-data processing technologies such as Apache Spark, Python, and cloud platforms.

Solid experience writing and optimizing SQL queries on large-scale and complex datasets.

Hands-on experience with PySpark DataFrames, Spark SQL, and Spark Streaming.

Production experience building and maintaining data pipelines.

Hands-on experience with SAP data integration / SAP data extraction.

Experience integrating SAP data with Databricks, Data Lake, Data Warehouse, or other cloud-based data platforms.

Experience with AWS / Azure / GCP.

Experience working in a DevOps and CI/CD environment.

Experience monitoring and troubleshooting data pipelines.

Databricks certification is optional/preferred.

Good to Have

Experience with SAP S/4HANA, SAP ECC, SAP BW/BW4HANA.

Experience with SAP integration tools/connectors such as SAP SLT, SAP Datasphere, SAP Data Services, SAP OData, or SAP APIs.

Experience with Hadoop, Kafka, Delta Lake, and Azure Data Factory.

Experience with Finance/ERP data and reporting.

Experience designing SAP-to-Databricks/cloud data pipelines.

Pay: ₹720,000.00 - ₹1,200,000.00 per year

Experience:

- SAP: 4 years (Required)
- SAP integration / SAP data extraction: 4 years (Required)

Work Location: Remote

📌 SAP DATA Analyst (India)
🏢 Arccus
📍 India