Data Engineer (Informatica & ETL/ELT)

Data Engineer (Informatica & ETL/ELT) Location: Riyadh, KSA (Onsite) Required Date: 25th October 2026 6 Months Contract Role Summary We are seeking a skilled and detail-oriented Data Engineer to design, build, and optimize robust data pipelines and integration workflows. In this role, you will be responsible for transforming raw data into structured, production-ready assets using Informatica and modern ETL/ELT methodologies. You will collaborate closely with data architects, platform admins, and analytics teams to ensure reliable, high-performance data delivery across the organization. Key Responsibilities • Data Pipeline Development: Design, build, test, and maintain efficient ETL/ELT data pipelines using Informatica to extract data from varied sources and load into targets. • Data Transformation & Modeling: Implement complex business logic, transformations, and data quality checks while adhering to scalable data modeling principles (Dimensional, Data Vault, or Star/Snowflake schemas). • Performance Tuning: Optimize SQL queries, database indexes, and Informatica mappings/workflows to maintain high performance across large volume datasets. • Pipeline Monitoring & Support: Monitor batch and real-time processing jobs, debug pipeline failures, resolve data discrepancies, and optimize resource usage. • Data Governance & Documentation: Maintain detailed data lineage, technical specifications, data dictionaries, and source-to-target mapping (STM) documentation. • Collaboration & Integration: Partner with platform admins for deployment and infrastructure optimization, and work with business analysts to translate business requirements into technical solutions. Required Technical Skills & Experience 1.1.1 Core Technical Stack • Informatica Expertise: Strong hands-on experience with Informatica (PowerCenter or IICS - Cloud Data Integration), including mapping design, workflow development, session tuning, and parameter files. • ETL/ELT Architecture: Deep understanding of ETL vs. ELT paradigms, incremental loading techniques, Change Data Capture (CDC), and slow-changing dimensions (SCD Types 1, 2, and 3). • Advanced SQL & Databases: Expert-level SQL skills for data extraction, manipulation, and query optimization across relational databases (e.g., PostgreSQL, Oracle, SQL Server, Snowflake, or Teradata). • Data Modeling: Proven experience designing target schemas, data marts, and working with both relational and analytical data warehouses. 1.1.2 Tooling & Automation • Scripting: Proficiency in Bash or Python for data processing, job orchestration, and automation. • Data Sources & Formats: Experience integrating structured, semi-structured, and unstructured data formats (JSON, Parquet, CSV, XML, REST APIs). • Scheduling & Version Control: Hands-on experience with enterprise schedulers (Automic, Control-M, Airflow) and version control tools (Git). 1.1.3 Experience Level • 5+ years of dedicated experience in data engineering, ETL development, or data integration. • Strong track record of translating complex business rules into reliable, production-grade data pipelines. • Familiarity with Agile/Scrum development methodologies. Preferred Qualifications • Informatica certifications (e.g., Informatica Certified Professional in PowerCenter or IICS). • Experience with cloud data platforms (Snowflake, Databricks, BigQuery, AWS Redshift). • Knowledge of streaming or real-time data pipelines (Kafka, Spark Streaming).

5+ years of dedicated experience in data engineering, ETL development, or data integration. Strong track record of translating complex business rules into reliable, production-grade data pipelines. Familiarity with Agile/Scrum development methodologies.

Data Pipeline Development: Design, build, test, and maintain efficient ETL/ELT data pipelines using Informatica to extract data from varied sources and load into targets. Data Transformation & Modeling: Implement complex business logic, transformations, and data quality checks while adhering to scalable data modeling principles (Dimensional, Data Vault, or Star/Snowflake schemas). Performance Tuning: Optimize SQL queries, database indexes, and Informatica mappings/workflows to maintain high performance across large volume datasets. Pipeline Monitoring & Support: Monitor batch and real-time processing jobs, debug pipeline failures, resolve data discrepancies, and optimize resource usage. Data Governance & Documentation: Maintain detailed data lineage, technical specifications, data dictionaries, and source-to-target mapping (STM) documentation. Collaboration & Integration: Partner with platform admins for deployment and infrastructure optimization, and work with business analysts to translate business requirements into technical solutions.