Data Engineer

Job Description

Work Set Up: Onsite

Key Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL workflows to support the enterprise lake house platform.
• Work closely with data scientists, analysts, and business teams to gather data requirements and deliver robust data solutions.
• Develop and implement data ingestion, transformation, and integration using big data technologies such as Hadoop, Spark, and Kafka.
• Manage and optimize data storage systems, including data lakes and warehouses, hosted on cloud platforms like AWS, Azure, or Google Cloud.
• Ensure high data quality, consistency, and dependability through comprehensive data validation and monitoring practices.
• Create and maintain clear documentation for data workflows, system architecture, and related processes.
• Diagnose and address data issues and performance inefficiencies.
• Keep up with emerging trends and advancements in big data and data engineering technologies.

Requirements:

• Bachelor's degree in computer science, Information Technology, or a related field.
• Proven experience as a Data Engineer, preferably in big data or cloud-based projects.
• Strong understanding of data lake and data warehouse concepts, architectures, and technologies.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (e.g., AWS, Azure, Google Cloud).
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Familiarity with data governance and security best practices.