Data Engineer

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About the Role:

Nuage Consulting is looking for a skilled Data Engineer to build and maintain robust data pipelines and infrastructure that empower our clients to make data-driven decisions. You will be responsible for designing, developing, and deploying scalable data solutions that support data warehousing, business intelligence, and advanced analytics initiatives. This role requires a strong understanding of data engineering principles, cloud data platforms, and programming skills.

Responsibilities:

• Data Pipeline Development: Design, develop, and maintain efficient and reliable data pipelines for data ingestion, transformation, and loading (ETL/ELT).
• Data Warehousing & Data Lakes: Build and maintain scalable data warehouses and data lakes on cloud platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery).
• Data Modeling & Database Design: Design and implement data models and database schemas that support business requirements and analytical needs.
• Data Quality & Governance: Implement data quality checks, data validation processes, and data governance policies to ensure data accuracy and reliability.
• Cloud Data Platform Expertise: Utilize and integrate cloud-based data services (e.g., AWS Glue, Azure Data Factory, Google Cloud Dataflow) into data engineering solutions.
• Automation & Scripting: Develop and maintain automation scripts (Python, SQL, etc.) for data processing, data validation, and pipeline management.
• Performance Optimization: Optimize data pipelines and database queries for performance, scalability, and efficiency.
• Collaboration: Work closely with data scientists, analysts, and other engineers to understand data requirements and deliver effective data solutions.
• Documentation: Create and maintain clear and concise documentation for data pipelines, data models, and data infrastructure.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
• Proven experience as a Data Engineer or similar role. 
• Strong understanding of data warehousing, ETL/ELT processes, and data modeling principles.
• Proficiency in SQL and experience with database technologies (e.g., relational databases, NoSQL databases).
• Experience with cloud-based data platforms and services (e.g., AWS, Azure, GCP).
• Strong programming skills in Python and experience with relevant libraries (e.g., Pandas, NumPy).
• Experience with data pipeline orchestration tools (e.g., Apache Airflow, Luigi).
• Knowledge of data quality and data governance best practices.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.
• Experience with data visualization tools is a plus.