Data Engineer

Job Responsibilities Include:

• Primary responsibility for our Data Platform
  • Data model ongoing design & development
  • Conceptual, logical and physical design (database, ODS, aggregates, etc.)
  • Database administration
  • Capacity analysis & management
• MDM Lead
  • Identify key domains that'd benefit from an MDM approach (e.g. Product, Customer), along with best data sources & necessary attributes, and integrate into the the platform
  • Define governance strategy with associated roles & responsibilities (e.g. Data Steward, Quality Specialist)
  • Define & implement Policies & SOPs
  • Monitor operations, develop and report quality metrics to key stakeholders
• Data Pipeline development:
  • Participate in Requirements Gathering: work with key business partner groups (e.g. Product Mgt) and other Data Engineering personnel to understand department-level data requirements for the the platform
  • Design Data Pipelines: work with other Data Engineering personnel on an overall design for flowing data from various internal and external sources into the the platform
  • Build Data Pipelines: leverage standard toolset and develop ETL/ELT code to move data from various internal and external sources into the the platform
• Support Data Quality Program: work with Data QA Engineer to identify automated QA checks and associated monitoring & alerting to ensure the platform maintains consistently high quality data
• Support Operations: triage alerts channeled to you and remediate as necessary
• Technical Documentation: leverage templates provided and create clear, simple and comprehensive documentation for your development
• Key contributor to defining, implementing and supporting:
  • Data Services
  • Data Dictionary
  • Tool Standards
  • Best Practices
  • Data Lineage
  • User Training
• Define Best Practices and Guidelines for other Data Engineering team members
• Lead the team in developing new technical skills necessary for cloud-native data engineering platform
  • Explores new tech
  • Shares and documents learnings
  • Productionalizes proof of concepts

Skills & Responsibilities:

• Expert Python
• Expert-level data modeler (back-end and semantic layer)
• Expert-level ETL/ELT designer/developer
• Strong database administration and operations experience & proficiency
• Strong SQL
• Structured & unstructured data expertise
• Cloud environment development & operations experience (e.g. Google Cloud Platform/GCP experience a plus)
• Excellent verbal and written communications
• Strong team player
• Working knowledge of eCommerce data a plus
• Prior experience with Git, Terraform, GCP Deployment Manager, CICD, Docker, Kubernetes, Apache Airflow, Apache Beam, Apache Spark experience is a plus

Success Criteria:

• Knowledge of data modeling concepts and data relationships
• Advanced Analytical Thinking and Problem Solving skills
• Solid experience in architecture, advanced reporting and dashboards
• Strong SQL skills and experience with performance tuning are required
• "Get it done” attitude with a high degree of autonomy, ownership and responsibility
• Superior Communication and Business-Technical Interaction skills

To qualify, you must possess the following skills:

• Bachelor's degree in computer science, management information systems, or a related discipline
• 5+ years hands-on data warehouse-data modeling experience
• 5+ years hands-on database admin/ops experience
• 5+ years hands-on ETL/ELT design/development experience
• Key resource on team(s) that have delivered successful enterprise-level analytics platforms

Recommended Skills

• Airflow
• Analytical
• Apache Http Server
• Apache Spark
• Architecture
• Backend