Data Engineer Support

Key Responsibilities

• Design, develop, and maintain ETL/ELT processes for data extraction, transformation, and loading.
• Build, optimize, and manage data pipelines to ensure efficient and reliable data processing.
• Develop and maintain SQL scripts, stored procedures, and database objects.
• Design and implement data models, data warehouses, and data architectures to support business needs.
• Perform data integration across multiple platforms and heterogeneous data sources.
• Utilize Apache Spark (PySpark, SparkR, or Scala) for large-scale data processing.
• Develop automation solutions for data workflows and integration processes.
• Collaborate with business users, analysts, and technical teams to gather requirements and deliver data solutions.
• Monitor, troubleshoot, and optimize ETL jobs and data pipelines to ensure performance and reliability.
• Ensure data quality, integrity, security, and compliance with organizational standards.
• Document technical designs, workflows, and operational procedures.

Requirements

• Minimum 1 year of experience in Data Engineering or a related field, or equivalent practical experience.
• Diploma or Bachelor's degree in Informatics Engineering, Computer Science, Information Systems, or a related field.
• Strong experience with SQL and database development.
• Experience using SQL Server Integration Services (SSIS).
• Hands-on experience with IBM InfoSphere products, including DataStage, Information Analyzer (IA), Business Process Manager (BPM), Rational Application Developer (RAD/Workbench), Performance Management Edition (PME), and DB2.
• Experience with Informatica Data Integration / Informatica PowerCenter or equivalent Informatica solutions.
• Experience using Apache Spark for data processing with PySpark, SparkR, or Scala.
• Proficiency in Python and/or R programming.
• Experience in designing and implementing ETL/ELT processes.
• Solid understanding of data modeling, data architecture, and data warehousing concepts.
• Knowledge of data integration, information management, data processing, and workflow automation across multiple platforms.
• Strong understanding of various database technologies, including relational and non-relational databases.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently as well as collaboratively in a team environment.

Skills: Redis, Data Integration, Python, ETL, Hadoop, Data Engineering, Data Processing, Database Systems, MongoDB, Microsoft SQL Server