Cloud Data Engineer V

Job Description:

The Cloud Data Engineer V works with business and IT stakeholders to develop modern, scalable data solutions that align with organizational strategy and architectural standards. This role is both autonomous and collaborative, requiring advanced technical expertise and leadership in supporting both existing data environments and new platform development. The engineer also acts as a subject matter expert and technical lead for the Cloud Data Engineering team.

Key Responsibilities:

• Provide technical direction and mentorship as the team lead for the Cloud Data Engineering function.
• Ensure alignment and optimization of solutions across platforms, in collaboration with architecture, infrastructure, and data teams.
• Conduct code and design reviews to enforce compliance with architectural standards.
• Troubleshoot and resolve technical issues while driving knowledge-sharing initiatives.
• Develop high-quality, maintainable, and testable code for complex data environments.
• Create automation tools to reduce manual intervention and improve operational efficiency.
• Build and manage robust systems to extract, transform, and load data from diverse sources.
• Translate business goals into appropriate, scalable cloud data solutions.
• Serve as subject matter expert for technologies such as MS SQL Server, Redshift, AWS Glue, DMS, Step Functions, Lambda, Iceberg tables, Athena, and AWS Data Pipelines.
• Design conceptual, logical, and physical cloud-based data architectures.
• Partner with software engineering and product teams to onboard new data sources and implement schema changes.
• Collaborate with BI and Data Science teams to develop insights and reporting frameworks.
• Perform environment-wide maintenance, monitoring, and troubleshooting of database platforms.
• Participate in an on-call support rotation for production systems.
• Use scripting tools such as Bash or PowerShell and interact with AWS via Boto3.
• Travel and in-person attendance may be required.
• Perform other responsibilities as assigned.

Education and Experience Required:

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 10+ years of experience in:
  • Cloud data platforms, big data, data lakes, and Lake Formation
  • ETL development, data modeling, and data architecture
  • Apache Spark, PySpark, and EMR
  • Python for data processing and scripting
  • Data warehouse architecture and optimization
  • AWS platform services across compute, containers, integration, storage, and DevOps

Preferred:

• AWS Certifications (Solutions Architect or Data Engineering)
• Experience building real-time streaming data pipelines
• Familiarity with microservices-based development in AWS
• Experience managing large data lakes or data warehouses
• Strong track record in designing and deploying end-to-end AWS solutions
• Prior leadership or people management experience

Skills & Abilities:

• Expert-level SQL writing and optimization
• Strong understanding of data quality, lineage, and discoverability
• Experience with distributed systems and lambda architectures
• Ability to build and optimize both batch and stream processing pipelines
• Strong analytical, debugging, and performance-tuning skills
• Ability to lead complex projects and manage shifting priorities
• Collaborative, team-oriented, and committed to shared success
• Detail-oriented and adaptable in dynamic, fast-paced environments
• Skilled at communicating technical concepts clearly to varied audiences
• Highly organized and self-motivated with a bias toward action
• Able to mentor others and cultivate a learning-focused culture
• Strong interpersonal and leadership presence with a balance of assertiveness and diplomacy