HAVI
About HAVI
HAVI is a global, privately owned company focused on innovating, optimizing and managing supply chains of leading brands. The company offers services in marketing analytics, packaging, supply chain management and logistics, and works with customers across more than 100 countries.
Job Overview Architect, design, implement, enhance, and maintain highly scalable, available, secure, and elastic cloud‑ready data solutions to support predictive and prescriptive analytics. Act as a trusted partner to solutions architects and data scientists, driving the analytics solution lifecycle from prototype to production and operations.
Location & Work Model This is a hybrid role based at 303-1 Concorde Gate North York, ON, M3C 3N6, Canada. Candidates must reside in the Toronto metropolitan area. Relocation assistance is not offered at this time.
Responsibilities
Work with data management, data science, decision science and technology teams to address supply‑chain data needs in demand/supply planning, replenishment, pricing and optimization.
Develop and refine data requirements, design and build data deliverables, and optimize data pipelines in both non‑production and production environments.
Design, build, and manage data pipelines, including data transformation, models, schemas, metadata, and workload management.
Integrate analytics and data science output into business processes and workflows.
Build and optimize data pipelines, architectures, and integrated datasets, covering ETL/ELT, data replication/CI/CD, API design, and access.
Work with and improve existing ETL processes and data integration flows, transitioning them to production.
Employ popular data discovery, analytics, BI and AI tools in semantic‑layer data discovery.
Apply agile methodologies and DevOps/DataOps principles to enhance communication, integration, reuse, and automation across data pipelines.
Implement Agentic AI capabilities to drive efficiency and opportunity.
Qualifications
Bachelor’s degree in computer science, data management, information systems or a related field; advanced degree preferred.
3+ years building production data pipelines (batch and/or streaming) with Spark on cloud.
2+ years hands‑on experience with Azure Databricks (PySpark/Scala, Spark SQL, Delta Lake), including Delta Lake operations, Unity Catalog, and Databricks Jobs/Workflows or Delta Live Tables.
Experience with Azure Data Factory for orchestration (pipelines, triggers, parameterization, IRs) and integration with ADLS Gen2 and Key Vault.
Strong SQL skills across large datasets; performance tuning (joins, partitions, file sizing).
Data quality at scale (e.g., Great Expectations/Deequ), monitoring, alerting, and debug/backfill playbooks.
DevOps for data: Git branching, code reviews, unit/integration testing (pytest/dbx), CI/CD (Azure DevOps/GitHub Actions).
Infrastructure as Code (Terraform or Bicep) for Databricks workspaces, cluster policies, ADF, storage.
Observability & cost control using Azure Monitor/Log Analytics; cluster sizing, autoscaling, Photon; cost/performance trade‑offs.
Proven experience collaborating with cross‑functional stakeholders (analytics, data governance, product, security) to ship and support data products.
Employee Benefits
Generous medical, dental, vision and other benefits.
Paid parental and medical leave programs.
401(k) with company match and profit sharing.
15 days of paid time off plus company holidays.
Hybrid work model with flexibility.
Tuition reimbursement and student loan repayment assistance.
Equal Opportunity Employer We are an equal opportunity employer and we value diversity. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will provide reasonable accommodation for individuals with disabilities.
Apply online with your salary expectations and earliest starting date.
#J-18808-Ljbffr
Job Overview Architect, design, implement, enhance, and maintain highly scalable, available, secure, and elastic cloud‑ready data solutions to support predictive and prescriptive analytics. Act as a trusted partner to solutions architects and data scientists, driving the analytics solution lifecycle from prototype to production and operations.
Location & Work Model This is a hybrid role based at 303-1 Concorde Gate North York, ON, M3C 3N6, Canada. Candidates must reside in the Toronto metropolitan area. Relocation assistance is not offered at this time.
Responsibilities
Work with data management, data science, decision science and technology teams to address supply‑chain data needs in demand/supply planning, replenishment, pricing and optimization.
Develop and refine data requirements, design and build data deliverables, and optimize data pipelines in both non‑production and production environments.
Design, build, and manage data pipelines, including data transformation, models, schemas, metadata, and workload management.
Integrate analytics and data science output into business processes and workflows.
Build and optimize data pipelines, architectures, and integrated datasets, covering ETL/ELT, data replication/CI/CD, API design, and access.
Work with and improve existing ETL processes and data integration flows, transitioning them to production.
Employ popular data discovery, analytics, BI and AI tools in semantic‑layer data discovery.
Apply agile methodologies and DevOps/DataOps principles to enhance communication, integration, reuse, and automation across data pipelines.
Implement Agentic AI capabilities to drive efficiency and opportunity.
Qualifications
Bachelor’s degree in computer science, data management, information systems or a related field; advanced degree preferred.
3+ years building production data pipelines (batch and/or streaming) with Spark on cloud.
2+ years hands‑on experience with Azure Databricks (PySpark/Scala, Spark SQL, Delta Lake), including Delta Lake operations, Unity Catalog, and Databricks Jobs/Workflows or Delta Live Tables.
Experience with Azure Data Factory for orchestration (pipelines, triggers, parameterization, IRs) and integration with ADLS Gen2 and Key Vault.
Strong SQL skills across large datasets; performance tuning (joins, partitions, file sizing).
Data quality at scale (e.g., Great Expectations/Deequ), monitoring, alerting, and debug/backfill playbooks.
DevOps for data: Git branching, code reviews, unit/integration testing (pytest/dbx), CI/CD (Azure DevOps/GitHub Actions).
Infrastructure as Code (Terraform or Bicep) for Databricks workspaces, cluster policies, ADF, storage.
Observability & cost control using Azure Monitor/Log Analytics; cluster sizing, autoscaling, Photon; cost/performance trade‑offs.
Proven experience collaborating with cross‑functional stakeholders (analytics, data governance, product, security) to ship and support data products.
Employee Benefits
Generous medical, dental, vision and other benefits.
Paid parental and medical leave programs.
401(k) with company match and profit sharing.
15 days of paid time off plus company holidays.
Hybrid work model with flexibility.
Tuition reimbursement and student loan repayment assistance.
Equal Opportunity Employer We are an equal opportunity employer and we value diversity. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will provide reasonable accommodation for individuals with disabilities.
Apply online with your salary expectations and earliest starting date.
#J-18808-Ljbffr