Ecommerce Data Architect & Analytics Engineer

Johnson Health Tech Companies

Town of Cottage Grove (WI)

On-site

USD 90,000 - 140,000

Full time

7 days ago

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Benefits offered by this job

Medical, dental, and vision insurance

Company-paid life insurance and AD&D

401(k) retirement savings plan

Paid time off (PTO)

FSA and HSA options

Employee product discounts

Job summary

Johnson Health Tech is seeking an Ecommerce Data & Analytics Engineer to build scalable data pipelines and dashboards across ecommerce, website analytics, CRM, marketing, and ERP. You will translate complex datasets into actionable business insights and work with cross-functional teams to improve visibility of customer journeys and growth opportunities.

The role emphasizes data modeling, reporting standards, and reliable data infrastructure to support data-driven decisions across the

Qualifications

Minimum 4-year degree or equivalent work experience.
Strong SQL, data modeling, and data visualization skills.
Experience with scalable data pipelines and ETL/ELT processes.
Experience with cloud data warehouses (Snowflake/BigQuery/Redshift).
Proficiency in Python and/or R for data transformation and analysis.
Experience integrating APIs and multiple data sources.
Experience with BI/reporting tools (Looker/Tableau/Power BI).
Knowledge of ecommerce analytics, attribution, and lifecycle marketing.

Responsibilities

Build and maintain scalable data pipelines connecting ecommerce, analytics, CRM, marketing, POS, ERP, and more.
Develop ETL/ELT processes to automate data ingestion, transformation, normalization, and reporting.
Establish reliable data models, schemas, and reporting standards for accuracy.
Integrate APIs and third-party data into centralized data and reporting environments.
Monitor data pipelines and reporting to resolve quality and performance issues.
Maintain documentation for data sources, definitions, integrations, and reporting structures.
Build centralized dashboards for ecommerce, customer lifecycle, showroom, marketing, product and category performance.
Combine behavioral, transactional, marketing, and operational data for a complete view of business performance.
Identify trends, anomalies, gaps, and growth opportunities; communicate findings to stakeholders.
Support data-driven decisions across cross-functional teams.