Full-Time Senior Data Engineer

The Senior Data Engineer reports to the Data Engineer Manager and designs, develops and supports ETL data pipeline solutions in the AWS environment.

• You will help build a semantic layer by developing ETL and virtualized views.
• Collaborate with engineering teams to discover and use new data that is being introduced into the environment.
• Work as part of a team to build and support a data warehouse and implement solutions using Python to process structured and unstructured data.
• Support existing ETL processes written in SQL, troubleshoot and resolve production issues.
• You will create report specifications and process documentation for the required data deliverables.
• Be a liaison between business and technical teams to achieve project goals, delivering cross-functional reporting solutions.
• Troubleshoot and resolve data, system, and performance issues.
• Communicate with partners, other technical teams, and management to collect requirements, articulate data deliverables, and provide technical designs.
• You have Experience providing engineering support to the customer support team to resolve any critical customer issues in an Agile environment.
• Experience communicating updates and resolutions to customers and other partners since, as a Data Engineer, you will collaborate with partners and technical teams.
• Minimum 5 years of experience as an ETL Data Engineer, and has intermediate knowledge working with SQL and data Experience approaching a problem from different angles, analyzing pros and cons of different solutions
• Minimum 5 years of experience in Python scripting
• Minimum 2 years of experience with AWS data ecosystem (Redshift, EMR, S3, MWAA, etc.)
• Minimum 3 years of experience working in an Agile environment.
• Highly motivated, self-starter, detail-oriented, and able to produce solutions.
• Experience with Tableau is a plus.Experience with DBT.
• Hands-on experience with Apache Airflow or equivalent tools (AWS MWAA) for the orchestration of data pipelines.
• Hands-on experience working and building with Python API-based data pipelines.