Senior Data Engineer
On-site 0081
Riyadh, Ar Riyāḍ, Saudi Arabia
Description
· Identifying and extracting data from various sources (such as databases, APIs, logs, files, and external systems).
· Ensuring data quality during extraction and handling any anomalies.
· Transforming raw data into a structured format suitable for analysis and reporting.
· Cleaning, aggregating, and enriching data using ETL tools and techniques.
· Implementing business rules and data validation logic.
· Loading processed data into data warehouses, data lakes, or other storage systems.
· Designing and maintaining ETL pipelines to move data efficiently.
· Collaborating with database administrators to optimize data loading processes.
· Designing, developing, and maintaining ETL workflows and pipelines.
· Writing efficient ETL code (Informatica PowerCenter & Informatica BDM) to automate data movement.
· Ensuring scalability, reliability, and performance of ETL processes.
· Profiling and tuning ETL processes for optimal performance. · Identifying bottlenecks and addressing them to improve data processing speed.
· Monitoring ETL jobs, identifying failures, and resolving issues promptly.
· Implementing error handling and logging mechanisms.
· Communicating effectively with cross-functional teams to understand data needs and ensure data consistency and accuracy.
Requirements
· Strong ETL Tool Proficiency
.Experience with ETL tools such as Informatica PowerCenter, Informatica BDM, and Apache NiFi.
· Database Knowledge
.Proficiency in SQL and understanding of relational databases (e.g., PostgreSQL, MySQL, Oracle).
· Data Warehousing: Familiarity with data warehousing concepts and technologies.
· Big Data Technologies: Exposure to big data platforms (e.g., Hadoop, Spark) and NoSQL databases (e.g., Hbase, MongoDB). · Data Governance and Security: Understanding of data governance practices and security protocols.
· Problem-Solving Abilities: Ability to troubleshoot complex data issues and optimize ETL processes.
· Excellent communication skills for technical and non-technical stakeholders.
· Experience in performance tuning for data queries.
· Understanding of data modelling and design standards, tools, and best practices.
· Analytical mind-set and problem-solving skills for proactive project support.
