
Data Engineer
5 days ago
Position: Data Engineer (AWS QuickSight, Glue, PySpark) (Noida) (CE46SF RM 3386)
Education Required: Bachelor's / Masters / PhD:
- Bachelor's or master's in computer science, Statistics, Mathematics, Data Science, Engineering
- AWS certification (e.g., AWS Certified Data Analytics – Specialty, AWS Certified Developer)
Must Have Skills
- Proficiency in AWS cloud services: AWS Glue, QuickSight, S3, Lambda, Athena, Redshift, EMR, and related technologies
- Strong experience with PySpark
- Expertise in SQL and data modeling for relational and non-relational databases
- Familiarity with business intelligence and visualization tools, especially Amazon QuickSight
Good To Have
- Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch).
- Understanding of MLOps and model deployment best practices.
- Hands-on experience with AWS services for ML.
- Experience or familiarity with HVAC domain is a plus
Key Responsibilities
- Design, develop, and maintain data pipelines using AWS Glue, PySpark, and related AWS services to extract, transform, and load (ETL) data from diverse sources
- Build and optimize data warehouse/data lake infrastructure on AWS, ensuring efficient data storage, processing, and retrieval
- Develop and manage ETL processes to source data from various systems, including databases, APIs, and file storage, and create unified data models for analytics and reporting
- Implement and maintain business intelligence dashboards using Amazon QuickSight, enabling stakeholders to derive actionable insights
- Collaborate with cross-functional teams (business analysts, data scientists, product managers) to understand requirements and deliver scalable data solutions
- Ensure data quality, integrity, and security throughout the data lifecycle, implementing best practices for governance and compliance5.
- Support self-service analytics by empowering internal users to access and analyze data through QuickSight and other reporting tools1.
- Troubleshoot and resolve data pipeline issues, optimizing performance and reliability as needed
Required Skills
- Proficiency in AWS cloud services: AWS Glue, QuickSight, S3, Lambda, Athena, Redshift, EMR, and related technologies
- Strong experience with PySpark for large-scale data processing and transformation
- Expertise in SQL and data modeling for relational and non-relational databases
- Experience building and optimizing ETL pipelines and data integration workflows
- Familiarity with business intelligence and visualization tools, especially Amazon QuickSight
- Knowledge of data governance, security, and compliance best practices.
- Strong programming skills in Python; experience with automation and scripting
- Ability to work collaboratively in agile environments and manage multiple priorities effectively
- Excellent problem-solving and communication skills.
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