Cloud Platform Engineer

About the role

Job Title: Cloud Platform Engineer
Experience: 7+ Years
Employment Type: Full-Time
Work Mode: Remote

Job Summary

We are seeking a highly skilled Cloud Platform Engineer / Cloud Data Engineer to join our team for a Cloud Data Modernization initiative.

The ideal candidate will have strong hands-on experience with Databricks, Azure Cloud data services, Apache Spark, PySpark, and Snowflake, with a proven background in migrating and modernizing on-premises ETL workloads to cloud-based data platforms.

Databricks is the primary data technology, with Snowflake as a secondary data platform. Candidates should also have experience with Azure and/or AWS cloud infrastructure and data services.

The role will involve designing and implementing modern cloud data solutions, developing scalable data pipelines, supporting ETL migrations, implementing DevOps and CI/CD practices, and ensuring data quality, security, observability, and performance.

Key Responsibilities

• Contribute to the migration and modernization of on-premises ETL workloads to Azure Cloud, Databricks, and Snowflake.
• Design, develop, and maintain scalable data engineering solutions using Databricks, Apache Spark, PySpark, and Python.
• Develop data pipelines using Azure Data Factory (ADF), Self-hosted Integration Runtime (SHIR), Logic Apps, ADLS Gen2, Blob Storage, and Snowflake.
• Review, analyze, and document existing on-premises ETL processes and data workflows.
• Translate legacy ETL processes into scalable and maintainable cloud-native solutions.
• Develop and optimize data ingestion, transformation, integration, and processing pipelines.
• Implement DevOps practices and CI/CD pipelines using GitHub Actions.
• Follow Git branching strategies, pull requests, code reviews, and software engineering best practices.
• Collaborate with architects, data engineers, application teams, QA, business stakeholders, and other cross-functional teams.
• Tune and optimize Databricks, Spark, PySpark, and Snowflake workloads for performance and scalability.
• Implement data quality validation, monitoring, reconciliation, and observability processes.
• Support automated data validation and reconciliation frameworks.
• Implement appropriate logging, monitoring, alerting, and operational processes for data pipelines.
• Ensure data solutions comply with organizational security, privacy, governance, and regulatory standards.
• Participate in Agile ceremonies, sprint planning, technical discussions, and delivery activities.
• Troubleshoot production issues and proactively identify performance, reliability, and data-quality problems.
• Leverage AI-assisted development tools to improve engineering productivity, code quality, testing, and documentation.
• Work independently, manage ambiguity, prioritize tasks, and deliver high-quality solutions within established timelines.

Primary Skills

• Databricks
• Azure Data Engineering
• Azure Data Factory (ADF)
• Self-hosted Integration Runtime (SHIR)
• Azure Data Lake Storage Gen2 (ADLS Gen2)
• Azure Blob Storage
• Logic Apps
• Apache Spark
• PySpark
• Python
• Snowflake
• ETL / ELT Development
• Cloud Data Migration
• Data Quality & Validation
• GitHub Actions
• CI/CD

Secondary Skills

• Delta Lake
• Lakehouse Architecture
• Medallion Architecture – Bronze / Silver / Gold
• Snowflake Data Engineering
• Data Modeling
• Database Design
• Airflow
• Data Governance
• Data Observability
• Performance Optimization
• AWS Cloud
• Azure Cloud
• AI/ML for Data Engineering
• AI-Assisted Development Tools
• Healthcare Payer Data

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
• Minimum 3+ years of experience as a Cloud Data Engineer, Cloud Platform Engineer, or similar role.
• Strong hands-on experience with Databricks in enterprise data engineering environments.
• Experience with Azure data services, particularly ADF, ADLS Gen2, Blob Storage, Logic Apps, and SHIR.
• Strong experience with Apache Spark and PySpark.
• Hands-on experience with Snowflake for data engineering or analytics workloads.
• Experience developing and supporting data migration and cloud modernization initiatives.
• Strong experience with ETL development using on-premises databases and ETL technologies.
• Strong SQL development skills, including:
• Complex queries
• Stored procedures
• Views
• Joins
• Data transformations
• Performance optimization
• Experience with Python or other scripting languages for data processing and automation.
• Hands-on experience with GitHub, including branching, pull requests, and code reviews.
• Experience implementing GitHub Actions and CI/CD pipelines.
• Experience supporting automated testing and data quality validation processes.
• Strong understanding of Agile/Scrum delivery methodologies.
• Ability to learn new technologies quickly and adapt to changing project requirements.
• Strong analytical, troubleshooting, communication, and collaboration skills.
• Ability to work independently and effectively manage ambiguity and competing priorities.
• Ability to work under tight deadlines and proactively escalate critical technical or delivery issues.
• Willingness to travel when required based on business needs and applicable travel conditions.

Preferred Qualifications

• Experience with Azure and/or AWS cloud platforms.
• Experience implementing Bronze/Silver/Gold (Medallion) architecture.
• Strong understanding of Delta Lake and Lakehouse architecture.
• Experience with Delta Lake optimization techniques.
• Experience with Databricks performance tuning and optimization.
• Experience with Snowflake performance optimization.
• Knowledge of enterprise data governance and data quality best practices.
• Experience with data modeling and database architecture.
• Experience with Airflow or other data orchestration frameworks.
• Experience developing Snowflake-based data engineering and analytics solutions.
• Experience leveraging AI/ML solutions for data engineering automation and workflow optimization.
• Familiarity with AI-assisted development tools such as GitHub Copilot, Databricks Assistant, ChatGPT, or Claude.
• Experience working with healthcare payer data, including:
• Claims
• Membership
• Enrollment
• Provider
• Clinical
• Financial data
• Azure or Databricks certification is a plus.

DevOps & Engineering Practices

• GitHub
• GitHub Actions
• CI/CD
• Git branching and pull requests
• Code reviews
• Automated testing
• Infrastructure and deployment automation
• Monitoring and observability
• Agile/Scrum

Key Competencies

• Cloud Data Engineering
• Databricks Engineering
• ETL Modernization
• Cloud Migration
• Azure Data Platform
• Spark & PySpark
• Snowflake
• Data Pipeline Development
• Data Quality & Reconciliation
• DevOps & CI/CD
• Performance Optimization
• Data Governance
• Problem Solving
• Technical Collaboration

Work Location: Remote

What you'll do

• Own delivery for client-facing web, mobile, AI, cloud or digital transformation work based on the role.
• Collaborate with project managers, designers, QA and client stakeholders through discovery, build, launch and support.
• Write clear documentation, communicate risks early and keep delivery quality high.
• Contribute to reusable engineering practices, reviews and mentoring inside the WebSenor team.

What we're looking for

• Strong hands-on experience relevant to this role and a portfolio of shipped production work.
• Clear communication, ownership mindset and ability to work with global clients.
• Comfort with delivery discipline: estimation, reviews, testing, documentation and release readiness.
• Ability to learn fast and work across modern product, engineering and AI-enabled workflows.

What you'll get

• Work on real enterprise client projects with measurable business outcomes.
• Collaborate with experienced engineering, design, QA and delivery teams.
• Growth through mentoring, project ownership and exposure to global clients.
• HR-approved compensation, benefits and policies as finalized during the offer process.

About the team

You will work with WebSenor project managers, UI/UX designers, QA engineers, cloud specialists and senior developers focused on quality delivery for enterprise clients.

Our hiring process

• Application Review: HR and delivery leadership review your profile for role fit.
• Technical Discussion: Meet the technical team for skill, communication and project-readiness evaluation.
• Final Conversation: Discuss compensation, joining timeline and team fit.
• Offer and Onboarding: Receive the offer, documentation checklist and onboarding plan.