Data Engineer

Leads the design and implementation of data infrastructure, driving the evolution of the company's data pipeline architecture to support advanced analytics and business insights. The position is responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The role is a self-directed position that is comfortable supporting the data needs of multiple teams, systems and products. Provides mentorship and guidance on best practices and software design principles.

The following are essential accountabilities:

Leads the creation and maintenance of optimal data pipeline architecture, ensures scalable, efficient, and secure data processing.

Assembles large, complex data sets that meet functional and non-functional business requirements.

Mentors and guides Data Engineer team members, promoting best practices and design principles.

Engages in advanced data modeling and architecture tasks.

Champions performance tuning, troubleshooting, and optimization of datasets to ensure efficient data delivery.

Identifies, designs, and implements internal process improvements: automates manual processes, optimizes data delivery, re-designs infrastructure for greater scalability, etc.

Designs and builds the infrastructure required for optimal extraction, transformation, and loading of data from a variety of data sources using SQL and big data technologies.

Builds analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.

Works with stakeholders including the Executive, Product, Data and Design teams to assist with data related technical issues and support their data infrastructure needs.

Works with data and analytics experts to strive for greater functionality in our data systems.

Responsible for managing complex queries for reporting and the application consumption.

Troubleshoots and provides root cause analysis for database software and data integrity issues.

Ability to work off-hours with occasional evenings, weekends, and/or holidays.

Minimum Education: Bachelor's degree in computer science or related experience.

Preferred Education: Master's degree in computer science or related experience.

Minimum Experience: 7 years as a Data Engineer.

Preferred Experience: 8 years as a Data Engineer.

Required Certification/ License: N/A

Preferred Certification/ License: AWS Data Engineer OR AWS Solution Architect certifications, Snowflake certifications.

Required Skills, Knowledge, and Experience:

Deep understanding of SQL and experience with multiple relational and NoSQL database solutions.

Expertise in optimizing ETL/ELT pipelines and data modeling.

Experience with version control systems and CI/CD pipeline development.

Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.

Experience supporting and working with cross-functional teams in a dynamic environment.

Demonstrated ability to lead projects and mentor junior team members.

Strong analytic skills related to working with unstructured datasets.

Develop processes and procedures supporting data transformation, data structures, metadata, dependency identification and workload management.

Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.

Strong project management and organizational skills.

Graduate Degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.

Experience with relational SQL (SQL Server) and NoSQL (Mongo) databases.