Data engineer
3 weeks ago
We are seeking a highly skilled Data Engineer to join our team at Nair-Systems in Bahrain.
Key Responsibilities:- Consolidate and analyze financial data, including budgets, income statement forecasts, Balance Sheet, and Profit and Loss.
- Design and develop stored procedures and ETL jobs to reconcile transactions and correct data discrepancies.
- Contribute to data warehouse design and management of relational database systems.
- Develop SQL Server T-SQL procedures/functions for batch processing and reporting based on user requirements.
- Create SAS EG and SAS DI jobs.
- Research and resolve discrepancies in financial data and manage the month-end close process.
- Solving complex problems.
- Testing and troubleshooting.
- Regulatory compliance.
- Financial reporting.
- ETL/ETT/ETM tools and processes.
- Risk management.
- Data warehouses and marts.
- Balance Sheet, Profit & Loss, Market Risk.
- Data modeling.
- SAS, SAS BI, MS SQL Server, T-SQL in data warehousing/batch processing.
- BE in Computer Science and Engineering.
- Professional Training in SQL Development, SAS EG, SAS DI, Object-oriented Programming (e.g., C#, Java).
- Experience with SAS Management Console, SAS DI, SAS Enterprise Guide, Base SAS, SAS Web Report Studio, SAS Delivery Portal, SAS OLAP Cube Studio, SAS Information Maps, SAS BI.
- Expertise in writing advanced SQL queries, stored procedures, and functions.
- Experience with ETL tools like SAS platform tools and Microsoft SQL Server.
- Understanding of Financial Reporting and Risk Reporting.
- Development within databases, specifically Microsoft SQL Server and/or Oracle.
- 3+ years of experience in relevant tools, including SAS Management Console, SAS DI, SAS Enterprise Guide, Base SAS, SAS Web Report Studio, SAS Delivery Portal, SAS OLAP Cube Studio, SAS Information Maps, SAS BI.
- Experience configuring/installing applications on servers (Windows/Linux/Unix) and basic knowledge of DNS, Ports, and Firewalls.
- Experience managing and developing distributed systems and clusters for batch and streaming data (Hadoop/Spark and/or Kafka/Flink).
- Experience handling semi-structured data sets (e.g., JSON, XML).
- Banking and Finance, Financial accounting, and Reporting Environment.
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