DE&A - Core - Cloud Data Engineering - Snowflake Data Engineering

Education

Experience

• 12+ years of experience in Data Engineering, Data Warehousing, or Big Data environments.
• Experience building and supporting large-scale enterprise data platforms.
• Experience working in Agile development environments.
• Education
• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related field.
• Programming Languages
• Python
• SQL
• Data Engineering Tools
• Apache Spark
• Databricks
• dbt
• Cloud Platforms
• Microsoft Azure
• AWS
• Google Cloud Platform (GCP)
• Data Platforms
• Snowflake
• Azure Synapse Analytics
• Amazon Redshift
• BigQuery
• Teradata
• Databases
• SQL Server
• Oracle
• PostgreSQL
• MySQL
• MongoDB
• Business Intelligence Tools
• Tableau
• Power BI
• Looker
• Qlik Sense
• DevOps & Version Control
• Git
• Azure DevOps
• Jenkins
• Terraform
• Docker
• Kubernetes

Programming Languages

Data Engineering Tools

Cloud Platforms

Data Platforms

Databases

Business Intelligence Tools

DevOps & Version Control

Preferred Skills

• Data Lakehouse Architecture
• Real-Time Streaming Architecture
• Data Mesh Concepts
• Master Data Management (MDM)
• Data Governance Frameworks
• Machine Learning Data Pipelines
• API Development & Integration
• Event-Driven Architecture
• Master's degree is a plus.
• Java (Preferred)
• Soft Skills
• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Ability to work independently and collaboratively within cross-functional teams.
• Strong documentation and presentation skills.
• Attention to detail and commitment to delivering high-quality solutions.
• Cloud Certifications
• Microsoft Azure Data Engineer Associate (DP-203)
• AWS Certified Data Analytics Specialty
• Google Professional Data Engineer
• Platform Certifications
• Snowflake SnowPro Certification
• Databricks Certified Data Engineer Associate
• Tableau Certified Professional (Preferred)

Soft Skills

Cloud Certifications

Platform Certifications

Data Pipeline Development

Data Platform Engineering

Data Quality & Governance

Performance Optimization

Collaboration & Stakeholder Engagement

DevOps & Automation

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Build and optimize batch and real-time data ingestion frameworks.
• Integrate data from multiple sources, including databases, APIs, SaaS applications, and third-party systems.
• Ensure data consistency, quality, and reliability across platforms.
• Develop and support enterprise Data Lake, Data Warehouse, and Lakehouse architectures.
• Implement scalable data solutions on cloud platforms.
• Design data models to support reporting, analytics, and AI/ML use cases.
• Optimize data storage, processing, and query performance.
• Establish data validation, cleansing, and monitoring processes.
• Implement data governance, lineage, cataloging, and metadata management practices.
• Ensure compliance with security, privacy, and regulatory requirements.
• Support audit and data quality initiatives.
• Monitor and tune data pipelines and databases for performance and scalability.
• Identify and resolve data bottlenecks and processing issues.
• Optimize SQL queries and large-scale data transformations.
• Collaborate with Data Architects to implement enterprise data solutions.
• Work closely with BI developers, analysts, and data scientists to support analytical needs.
• Participate in requirements gathering, solution design, and technical reviews.
• Provide production support and troubleshooting for critical data platforms.
• Implement CI/CD pipelines for data engineering solutions.
• Automate deployment, monitoring, and operational processes.
• Support infrastructure-as-code and cloud automation initiatives.