Data Engineer
Role details
Job location
Tech stack
Job description
Responsible for working with the data management, data science, decision science, and technology teams to address supply chain data needs in demand and supply planning, replenishment, pricing, and optimization
Develop/refine the data requirements, design/develop data deliverables, and optimize data pipelines in non-production and production environments
Design, build, and manage/monitor data pipelines for data structures encompassing data transformation, data models, schemas, metadata, and workload management. The ability to work with both IT and business
Integrate analytics and data science output into business processes and workflows
Build and optimize data pipelines, pipeline architectures, and integrated datasets. These should include ETL/ELT, data replication/CI-CD, API design, and access
Work with and optimize existing ETL processes and data integration and preparation flows and help move them to production
Work with popular data discovery, analytics, and BI and AI tools in semantic-layer data discovery
Adept in agile methodologies and capable of applying DevOps and DataOps principles to data pipelines to improve communication, integration, reuse, and automation of data flows between data managers and data consumers across the organization
Implement Agentic AI capability to drive efficiency and opportunity, HAVI does not accept agency resumes submitted by third-party vendors unless a valid agreement has been signed and the HAVI Talent Acquisition Team has granted authorization for submissions for a specified position. Please do not submit or forward resumes to our site, HAVI employees, or any other company location. HAVI is not responsible for any fees related to unsolicited resumes.
Requirements
Bachelor's degree in computer science, data management, information systems, information science or a related field; advanced degree in computer science, data management, information systems, information science or a related field preferred.
3+ years in data engineering building production data pipelines (batch and/or streaming) with Spark on cloud.
2+ years hands-on Azure Databricks (PySpark/Scala, Spark SQL, Delta Lake) including:
Delta Lake operations (MERGE/CDC, OPTIMIZE/Z-ORDER, VACUUM, partitioning, schema evolution).
Unity Catalog (RBAC, permissions, lineage, data masking/row-level access).
Databricks Jobs/Workflows or Delta Live Tables.
Azure Data Factory for orchestration (pipelines, triggers, parameterization, IRs) and integration with ADLS Gen2, Key Vault.
Strong SQL across large datasets; performance tuning (joins, partitions, file sizing).
Data quality at scale (e.g., Great Expectations/Deequ), monitoring and alerting; 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: Azure Monitor/Log Analytics; cluster sizing, autoscaling, Photon; cost/perf trade-offs.
Proven experience collaborating with cross-functional stakeholders (analytics, data governance, product, security) to ship and support data products.
Dimensions & Stakholders: Content scope: Data engineering, data modeling, Agentic AI and automation, and data solution operationalization
Benefits & conditions
345 North Morgan Street, Chicago, IL 60607 Hybrid work $100,000 - $115,000 a year
Full-time, Pulled from the full job description Loan assistance Tuition reimbursement Paid parental leave Parental leave Health insurance 401(k) matching Paid time off, Working model: Individual contributor, collaborates with cross-functional team within global planning and analytics
- Starting Salary is $100,000-$115,000 with a 5% targeted bonus
TOTAL REWARDS
Our total rewards philosophy integrates programs for compensation, benefits, recognition, learning and development, corporate culture, corporate citizenship and work-life balance. While individual program components may differ by country, some things remain constant:
Our commitment to rewarding results
Opportunities to work with talented and driven individuals at every level of our company who respect each other, treat each other fairly and hold one another accountable for our customers'-and our company's-success
There's more ...
Inclusive employee resource groups
Generous medical, dental, vision and other great benefits
Paid parental and medical leave programs
401(k) with a company match component and profit sharing
15 days of paid time off plus company holidays
Hybrid work model with flexibility
Tuition reimbursement and student loan repayment assistance