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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