Data Engineer 1

Cypress HCM; San Jose (CA); Hybrid; USD 86,000 - 122,000; Full time

Job summary

Cypress HCM in San Jose, CA hybrid is seeking a Cloud & Data Engineer to help build, optimize, and operate our VoC AI Platform. The role spans data engineering, cloud infra, and platform reliability, with a strong Azure Databricks and Python skill focus.

You will own ETL/ELT pipelines, refine data processing workloads, and ensure secure data storage and governance. The position offers hands-on cloud infra work and collaboration across AI/ML teams.

Qualifications

• 3–5 years of experience in data engineering, cloud engineering, or a related role.
• Hands-on experience with Microsoft Azure, Databricks, APIs, and object storage.
• Strong skills in Python/PySpark and SQL.
• Experience building and operating production data ETL/ELT pipelines.
• Experience with relational and semi-structured/unstructured data and database technologies.
• Experience with Spark, Delta Lake, and lakehouse architectures.
• Working knowledge of Databricks Unity Catalog and data-access controls.
• Understanding of cloud security concepts such as RBAC, managed identities, service principals, and Key Vault.
• Experience with Git, CI/CD, monitoring, troubleshooting, and performance optimization.

Responsibilities

• Data Engineering: Build and maintain ETL/ELT pipelines for structured and unstructured data sources.
• Data Engineering: Develop data-processing workloads using Azure Databricks, Python/PySpark, and SQL.
• Data Engineering: Optimize Databricks jobs, compute, and data layouts for performance and cost.
• Data Engineering: Work with Delta Lake and Unity Catalog for data storage, governance, and access control.
• Data Engineering: Implement data quality checks, monitoring, error handling, and recovery mechanisms.
• Cloud & Platform Engineering: Build, operate, and optimize Azure services including App Service, Functions, Blob/ADLS storage, Azure SQL DB for Postgres, Key Vault, Container Registry and Azure Monitor.
• Cloud & Platform Engineering: Experience with cloud AI services including vector search and embedding pipelines.
• Cloud & Platform Engineering: Improve platform performance, scalability, reliability, security, and cost efficiency.
• Cloud & Platform Engineering: Implement secure identity and access management using Azure managed identities, Key Vault, and service principals.
• Automation & Operations: Improve platform observability through logging, monitoring, dashboards, and alerting.
• Automation & Operations: Automate infrastructure and deployments using Infrastructure as Code (IaC) and CI/CD.
• Automation & Operations: Troubleshoot issues across cloud services, storage, databases, networking, and data pipelines.
• Automation & Operations: Support production incidents and perform root-cause analysis.
• Collaboration: Collaborate with application, AI/ML, and data engineering teams.

Skills

Python

PySpark

SQL

Data pipelines

Cloud engineering

Monitoring & troubleshooting

Tools

Microsoft Azure

Databricks

Unity Catalog

Key Vault

Terraform

Azure DevOps

GitHub Actions

Airflow

ARM templates

Databricks Workflows

Job description

Job Details

• Duration: 11/16/2026 - 11/15/2027 (Contract)
• Data Engineer 1
• Location: San Jose, CA 95110 (Hybrid)
• Duration: 11/16/2026 - 11/15/2027 (Contract)
• Team: C&P Biz Ops- Strategy & Biz Ops

Job Overview

• We are looking for a Cloud & Data Engineer to help build, optimize, and operate our Voice of Customer (VoC) AI Platform.
• The platform ingests structured and unstructured data from multiple enterprise sources with varying degrees of signal-to-noise ratio and is primarily built on Microsoft Azure, with data processing and ETL/ELT workloads powered by Azure Databricks.
• This is a hands-on role spanning data engineering, cloud infrastructure, and platform reliability.

Responsibilities

• Data Engineering: Build and maintain ETL/ELT pipelines for structured and unstructured data sources.
• Data Engineering: Develop data-processing workloads using Azure Databricks, Python/PySpark, and SQL.
• Data Engineering: Optimize Databricks jobs, compute, and data layouts for performance and cost.
• Data Engineering: Work with Delta Lake and Unity Catalog for data storage, governance, and access control.
• Data Engineering: Implement data quality checks, monitoring, error handling, and recovery mechanisms.
• Cloud & Platform Engineering: Build, operate, and optimize Azure services including App Service, Functions, Blob/ADLS storage, Azure SQL DB for Postgres, Key Vault, Container Registry and Azure Monitor.
• Cloud & Platform Engineering: Experience with cloud AI services including vector search and embedding pipelines.
• Cloud & Platform Engineering: Improve platform performance, scalability, reliability, security, and cost efficiency.
• Cloud & Platform Engineering: Implement secure identity and access management using Azure managed identities, Key Vault, and service principals.
• Cloud & Platform Engineering: Support development, staging, and production environments.
• Automation & Operations: Improve platform observability through logging, monitoring, dashboards, and alerting.
• Automation & Operations: Automate infrastructure and deployments using Infrastructure as Code (IaC) and CI/CD.
• Automation & Operations: Troubleshoot issues across cloud services, storage, databases, networking, and data pipelines.
• Automation & Operations: Support production incidents and perform root-cause analysis.
• Collaboration: Collaborate with application, AI/ML, and data engineering teams.

Required Qualifications

• 3–5 years of experience in data engineering, cloud engineering, or a related role.
• Hands-on experience with Microsoft Azure, Databricks, APIs, and object storage.
• Strong skills in Python/PySpark and SQL.
• Experience building and operating production data ETL/ELT pipelines.
• Experience with relational and semi-structured/unstructured data and database technologies.
• Experience with Spark, Delta Lake, and lakehouse architectures.
• Working knowledge of Databricks Unity Catalog and data-access controls.
• Understanding of cloud security concepts such as RBAC, managed identities, service principals, and Key Vault.
• Experience with Git, CI/CD, monitoring, troubleshooting, and performance optimization.

Preferred Qualifications

• Experience with Terraform or ARM templates.
• Experience with Azure DevOps or GitHub Actions.
• Familiarity with Azure networking, including VNets and private endpoints.
• Experience with Azure Data Factory, Databricks Workflows, or Airflow.
• Familiarity with data platforms supporting AI/ML, NLP, analytics, or GenAI applications.

Compensation

• Pay Rate: $75.35/hour