Responsibilities
- Develop and manage scalable data architectures, pipelines, and modeling approaches supporting the enterprise data warehouse on AWS
- Design and oversee data models and schemas using Redshift and related technologies to enable independent analytics access
- Oversee, enhance, and resolve issues in data processing jobs to maintain reliable performance and uptime
- Establish data validation processes, quality controls, and alert systems to ensure data accuracy and dependability
- Utilize AWS tools such as Glue, Lambda, S3, Athena, and EMR to create flexible and reusable data workflows
- Collaborate with data science, analytics, and business units to identify data requirements, prioritize initiatives, and deliver accurate datasets
- Advance data lineage tracking, metadata cataloging, and documentation practices for greater transparency and reuse
- Produce and update technical documentation and version-controlled development processes using tools like Git and dbt
- Support a culture of ongoing improvement by mentoring colleagues and promoting scalable, modern data engineering standards
- Engage in Agile practices including sprint planning, peer code reviews, and team retrospectives
- Encourage the use of reusable components, modular architecture, and automation to support future growth
- Stay informed about advancements in data technology to uncover opportunities for innovation and efficiency
Work Arrangement
Hybrid — NYC
Other
You will be in office 4 times a week
