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Description supplied by the original job listing.
About the Role
We are looking for a passionate Data Engineer with 5+ years of experience in designing,
developing, and maintaining scalable data platforms and ETL/ELT pipelines. The ideal candidate
should possess strong expertise in Python, SQL, cloud data services, and modern data
engineering frameworks. You will play a key role in building reliable, high-performance data
solutions that support analytics, reporting, and AI/ML initiatives.
Key Responsibilities
• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and optimize data ingestion processes from multiple structured and unstructured
data sources.
• Develop robust data models and data warehouses for analytics and reporting.
• Design and optimize SQL queries for high-performance data processing.
• Build and maintain data lakes using cloud storage solutions.
• Implement data validation, cleansing, transformation, and quality checks.
• Integrate data solutions with cloud platforms such as AWS, Azure, or Google Cloud
Platform.
• Develop batch and real-time data processing pipelines using modern data processing
frameworks.
• Collaborate with data scientists, analysts, and application teams to deliver reliable data
solutions.
• Follow software engineering best practices, including Git, CI/CD pipelines, testing,
monitoring, and technical documentation.
Required Skills
• 5+ years of experience in Data Engineering.
• Strong programming experience in Python.
• Hands-on experience with PySpark and Apache Spark.
• Advanced SQL skills, including query optimization and performance tuning.
• Experience with AWS services/ Azure/ GCP.
• Experience building scalable ETL/ELT pipelines.
• Strong exp in Generative AI and Large Language Models (LLMs)
• Knowledge of data warehousing concepts and dimensional modeling.
• Experience working with large-scale distributed datasets.
• Familiarity with Git and CI/CD pipelines.
• Understanding Agile/Scrum methodologies.
Preferred Qualifications
• Experience with Apache Airflow or similar workflow orchestration tools.
• Knowledge of Kafka and real-time data streaming.
• Familiarity with Docker, Kubernetes, and Terraform (IaC).
• Exposure to Databricks and modern data lake technologies (Delta Lake, Apache Iceberg,
or Apache Hudi).
• Understanding data governance, metadata management, and CI/CD practices.
• Strong exp in Generative AI and Large Language Models (LLMs
Work arrangement
No
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