GMS-Senior Manager-Data Architect

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SAP S/4 HANA FICO Architect with Data architect capability

 

The SAP S/4 HANA FICO Data Architect is responsible for designing and implementing financial solutions based on Data analytics platform that support the organization's financial reporting requirements. This role involves a deep understanding of finance operations, SAP FICO modules, Integration with other modules and the technical capabilities of the SAP S/4 HANA integration capability. This role expecting to work closely with ETL developer, data engineering, and Data architect team to build robust analytic solution for financial reporting. The applicant must have a mix of skills of SAP FICO and Databricks which will enable him/her to effectively work with SAP HANA tables and build robust ETL pipelines within the Databricks environment.

 

Key Responsibilities:

• Lead the design and architecture of SAP FICO Reporting solutions on Databricks platform, ensuring they meet business requirements and performance goals.
• Collaborate with stakeholders to understand financial reporting ask and develop a roadmap for the same.
• Architect scalable SAP FICO modules reporting, including General Ledger, Accounts Payable, Accounts Receivable, Asset Accounting, and Controlling modules.
• Design harmonized data modelling solutions with multiple ERP sources including SAP and Oracle ERPs.
• Oversee data migration, system upgrades, and testing activities to ensure data integrity and system stability.
• Design and implement scalable ETL pipelines using Databricks and Apache Spark.
• Extract data from various sources, including SAP HANA tables, and transform and load it into the desired format for analysis.
• Develop and maintain Databricks notebooks for data processing and workflow orchestration.
• Monitor ETL jobs to ensure performance, reliability, and data quality.
• Collaborate with data architects to model data and design data warehouse schemas.
• Work closely with data scientists and analysts to understand data requirements and deliver the necessary data structures.
• Ensure compliance with data security and privacy standards.
• Document ETL processes, including data lineage and transformations.
• Stay up-to-date with the latest advancements in SAP FICO, Databricks and data engineering best practices.

 

Applicant is expected to have below mention Qualifications & Skills:

Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.

 

SAP FICO Knowledge:

• Understanding of financial processes and accounting principles.
• Experience with financial reporting and analysis
• Proficiency in SAP FI (Financial Accounting) modules, including General Ledger (GL),    Accounts Payable (AP), Accounts Receivable (AR), Asset Accounting (AA), and Bank Accounting.
• Proficiency in SAP CO (Controlling) modules, including Cost Element Accounting, Cost Centre Accounting, Internal Orders, Product Costing, and Profitability Analysis.
• Knowledge of integration points with other SAP modules like MM (Materials Management), SD (Sales and Distribution), and PP (Production Planning).

 

SAP HANA Knowledge:

• Basic understanding of SAP HANA tables and data structures.
• Familiarity with SAP HANA SQL and SQLScript for querying and data manipulation.
• Experience with connecting to SAP HANA databases from external systems.

 

Databricks Platform Knowledge:

• Understanding of Databricks Unified Analytics Platform.
• Experience with Databricks notebooks, jobs, and clusters.
• Knowledge of Databricks utilities like DBUtils.

 

Apache Spark:

• Proficiency in Apache Spark for large-scale data processing.
• Ability to write Spark SQL queries for data transformation.
• Experience with Spark DataFrames and Datasets for ETL operations.
• Familiarity with Spark architecture and optimization techniques.

 

Programming Languages:

• Proficiency in Scala, Python, or Java for writing Spark jobs.
• Ability to write UDFs (User Defined Functions) in Spark.

 

ETL Process:

• Experience in designing and implementing ETL pipelines.
• Understanding of data modeling, data warehousing, and data architecture.
• Knowledge of ETL best practices and performance tuning.

 

Data Sources and Integration:

• Experience with various data sources such as JSON, CSV, Parquet, etc.
• Knowledge of data ingestion methods from different databases and APIs.
• Ability to integrate with various data storage systems like S3, Azure Blob Storage, HDFS, etc.

 

Cloud Platforms:

• Understanding of cloud services related to data storage and computation (AWS, Azure, GCP).
• Experience with cloud-based Databricks deployment.

 

Version Control and CI/CD:

• Familiarity with version control systems like Git.
• Understanding of CI/CD pipelines for deploying ETL jobs.

 

Monitoring and Logging:

• Experience with monitoring ETL jobs and pipelines.
• Knowledge of logging and debugging techniques in Databricks and Spark.

 

Security and Compliance:

• Understanding of data security, encryption, and compliance standards.
• Familiarity with role-based access control within Databricks.

 

Collaboration and Communication:

• Ability to work in a team and collaborate with data scientists, analysts, and business stakeholders.
• Strong problem-solving skills and effective communication.

 

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