Sr. AWS Data Engineer with ETL Development || Livonia, MI (Hybrid)---Locals Only

DMS Vision•Frisco, AL

1d•Hybrid

About The Position

The Sr. AWS Data Engineer translates business needs into ETL and reporting requirements and provides guidance on data usage and interpretation. The role designs and implements reliable, accurate, and timely data pipelines using DBT, Python, and GitHub, and enhances development and implementation environments through custom DBT libraries and Python and shell scripts. The engineer monitors daily job execution, resolves issues to meet stakeholder SLAs, improves data warehouse design and data collection, and develops reports and dashboards to answer business questions with minimal latency. The position collaborates with product and engineering, governance, security, cloud engineering, data platform, analytics, and IT teams to address data requirements, configure Docker images, and align reporting solutions with change management, performance, and access needs. The position is hybrid in Livonia, Michigan, and is listed for a duration of 12+ months.

Requirements

Bachelor's degree in Engineering, Computer Science, Math, or a related technical field.
At least 7 years of experience in data engineering and analytics, focused on ETL development, data modeling, and data analysis.
Expertise in SQL and ETL optimization, particularly in cloud data warehouses such as Snowflake, BigQuery, and Redshift.
Experience using command-line tools and version control software such as Git.
Experience with cloud-based data storage solutions such as AWS S3, Azure Blob Storage, or Google Cloud Storage.
Proficiency in Python, including Pandas and NumPy.
Ability to use tools, business intuition, and attention to detail for data validation and quality assurance.
Excellent communication skills, especially when explaining technical or complex matters to less technical coworkers.
High motivation and a proactive approach to work.
Understanding of major marketing channels, such as TV, direct mail, social media, and search.
Experience mentoring and guiding junior data engineers and analysts.

Nice To Haves

Familiarity with data schemas and logging for marketing platforms such as Salesforce, Adobe Campaign, and Google Analytics.

Responsibilities

Translate business needs into ETL and report requirements, and advise and educate users on data usage and interpretation.
Diagram complex technical processes and translate abstract problems into discrete technology actions.
Design and implement data pipelines using DBT, Python, and GitHub according to software and data engineering best practices.
Enhance development and implementation environments by implementing custom DBT libraries and writing or modifying Python and shell scripts.
Monitor daily job execution and resolve issues to ensure internal stakeholder SLAs are met.
Improve data warehouse design using data modeling best practices and identify gaps in data collection capabilities.
Collaborate with product and engineering, governance, and security teams on data capture, retention, and security requirements.
Develop reports and dashboards that answer key business questions clearly, accurately, and with minimal latency.
Work with Cloud Engineering to configure Docker images.
Coordinate with Data Platform Engineering, Enterprise Data Analyst, Data Governance, and IT teams to align with change management processes and optimize reporting solution performance, processes, and access.