Cloud Data Engineer - Cloud Platforms, ETL/ELT & Big Data Systems
Skills:
Cloud Data Engineering | AWS | Azure | GCP | ETL/ELT | Big Data | Data Warehousing | Data Pipelines | Data Governance
Department: Data Engineering / Cloud Platform
Employment Type: Full Time
Work Mode: Onsite / Hybrid / Remote
Experience: 5-10 Years
About the Role
We are seeking a highly skilled Cloud Data Engineer to design, build, and maintain scalable, high-performance data pipelines across cloud platforms.
This role focuses on enabling data-driven decision-making by ensuring efficient data ingestion, transformation, storage, and accessibility for analytics and business intelligence. You will work with large volumes of structured and unstructured data, contributing to enterprise-scale data architecture and cloud transformation initiatives.
Key Responsibilities
Data Pipeline Development & Optimization
- Design, build, and maintain scalable ETL/ELT pipelines across cloud environments
- Process large-scale structured and unstructured datasets efficiently
- Optimize pipelines for performance, reliability, and cost efficiency
Cloud Data Architecture
- Develop and manage cloud-native data solutions using AWS, Azure, or GCP
- Work with data warehouses such as Redshift, BigQuery, Snowflake, or Synapse
- Design and implement data lake and data warehouse architectures
Data Engineering & Processing
- Build robust data workflows using Python, SQL, and Spark (PySpark)
- Develop batch and real-time data processing pipelines
- Ensure high data quality, integrity, and consistency across systems
Data Orchestration & Automation
- Implement orchestration workflows using Apache Airflow or similar tools
- Automate data ingestion, transformation, and deployment pipelines
- Support CI/CD practices for data engineering workflows
Monitoring, Performance & Troubleshooting
- Monitor pipeline performance and resolve bottlenecks
- Optimize query performance and data processing efficiency
- Ensure system reliability through proactive issue resolution
Security, Compliance & Governance
- Implement data security, encryption, and access control mechanisms
- Ensure compliance with data privacy and regulatory standards
- Support data governance, metadata management, and auditing processes
Collaboration & Cross-Functional Work
- Collaborate with data scientists, analysts, and engineering teams
- Enable data access for analytics, reporting, and machine learning use cases
- Support enterprise-wide data initiatives and platform integrations
Cloud Migration & Innovation
- Support cloud migration and modernization initiatives
- Evaluate new tools and technologies for data engineering improvements
- Contribute to proof-of-concept (POC) and architecture design decisions
Technical Skills
Programming & Data Processing
- Required: Python, SQL
- Preferred: PySpark, Scala, Java
Databases & Data Management
- Relational databases: PostgreSQL, MySQL, SQL Server
- Cloud data warehouses: Redshift, BigQuery, Snowflake, Synapse
- Experience with data lake architectures
Cloud Technologies
- AWS, Azure, or GCP
- Cloud-native storage, compute, and data services
Frameworks & Tools
- Apache Spark, Hadoop ecosystem
- Data integration tools (Apache NiFi or similar)
Orchestration & DevOps
- Airflow, Terraform, CloudFormation
- Jenkins, Git, Docker, Kubernetes
Security & Compliance
- Data masking, encryption, IAM
- Compliance frameworks (GDPR, HIPAA, or equivalent)
Experience Requirements
- 5+ years of experience in cloud data engineering and pipeline development
- Proven experience with ETL/ELT processes and large-scale data systems
- Hands-on experience with cloud data platforms and warehouses
- Experience optimizing data workflows for scalability and performance
- Exposure to cloud migration and infrastructure automation preferred
Day-to-Day Responsibilities
- Design and implement scalable data pipelines
- Collaborate with cross-functional teams on data workflows
- Automate ingestion and transformation processes
- Troubleshoot pipeline issues and optimize performance
- Ensure data security and governance compliance
- Support cloud migration and modernization projects
- Maintain documentation and architecture diagrams
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Engineering, or related field
- Certifications in cloud data platforms (AWS / GCP / Azure) preferred
- Experience working in enterprise-scale or regulated environments is a plus
Professional Competencies
- Strong analytical and problem-solving skills
- Excellent communication and collaboration abilities
- Ability to manage multiple priorities in fast-paced environments
- Leadership mindset with mentoring capabilities
- Strategic thinking for scalable and secure data architecture
- Continuous learning mindset with adaptability to new technologies
Why This Role is High Impact
- Work on large-scale cloud data platforms and enterprise systems
- Enable data-driven decision-making across business functions
- Build high-performance, scalable data infrastructure
- Contribute to digital transformation and modernization initiatives
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