Seeking a hands-on Senior Data Engineer Consultant to rapidly design, build, and deploy scalable enterprise data products. The successful consultant will combine strong technical depth with a bias for action, end-to-end ownership, and disciplined delivery.
Design, develop, test, review and support enterprise data pipelines using Snowflake, Azure Data Factory, Azure Data Lake Storage, SQL, and Python.
Build and optimize bronze, silver, and gold data products using scalable ETL/ELT, data modeling, orchestration, and data quality practices.
Translate business requirements into production-ready technical solutions, delivering from design through deployment and support.
Implement automated testing, CI/CD, DevSecOps, DataOps, monitoring, audit controls, and pipeline observability.
Troubleshoot UAT and Production issues, perform root-cause analysis, and implement sustainable fixes.
Create reusable engineering patterns and clear technical documentation; collaborate effectively in Agile teams with architects, product owners, engineers, and business stakeholders.
Comfortable using AI to develop using specs - design, code, build and review production grade pipelines.
Snowflake; Azure Data Factory; Azure Data Lake Storage
Advanced SQL; Python; ETL/ELT; pipeline orchestration
Data warehousing; dimensional modeling; medallion architecture
Performance tuning; data quality; observability; production support
Git; CI/CD; automated testing; Agile delivery
10+ years of hands-on data engineering experience delivering production-grade pipelines and enterprise data products.
Proven ability to work independently, manage technical risks and dependencies, and deliver committed outcomes with minimal supervision.
Strong problem-solving, communication, and stakeholder collaboration skills in a fast-paced global environment.
Demonstrated focus on automation, scalability, maintainability, and measurable business value.
Power BI, semantic modeling, or analytics enablement.
Jira, Azure DevOps, ServiceNow, Control-M, or equivalent engineering and delivery tools.
AI-assisted development, agentic workflows, and modern data product architectures.
Commercial, customer, quality, field-service, or operational reporting data products.
Duration: 4 months with potential to extend into 2027.
Capacity: Full-time, approximately 40 hours per week
Location: One consultant in the United States (U.S. citizenship required) and one consultant in India
Working Model: Regular overlap with US business hours for Agile ceremonies, design reviews, and stakeholder collaboration
Seeking a hands-on Senior Data Engineer Consultant to rapidly design, build, and deploy scalable enterprise data products. The successful consultant will combine strong technical depth with a bias for action, end-to-end ownership, and disciplined delivery.
Design, develop, test, review and support enterprise data pipelines using Snowflake, Azure Data Factory, Azure Data Lake Storage, SQL, and Python.
Build and optimize bronze, silver, and gold data products using scalable ETL/ELT, data modeling, orchestration, and data quality practices.
Translate business requirements into production-ready technical solutions, delivering from design through deployment and support.
Implement automated testing, CI/CD, DevSecOps, DataOps, monitoring, audit controls, and pipeline observability.
Troubleshoot UAT and Production issues, perform root-cause analysis, and implement sustainable fixes.
Create reusable engineering patterns and clear technical documentation; collaborate effectively in Agile teams with architects, product owners, engineers, and business stakeholders.
Comfortable using AI to develop using specs - design, code, build and review production grade pipelines.
Snowflake; Azure Data Factory; Azure Data Lake Storage
Advanced SQL; Python; ETL/ELT; pipeline orchestration
Data warehousing; dimensional modeling; medallion architecture
Performance tuning; data quality; observability; production support
Git; CI/CD; automated testing; Agile delivery
10+ years of hands-on data engineering experience delivering production-grade pipelines and enterprise data products.
Proven ability to work independently, manage technical risks and dependencies, and deliver committed outcomes with minimal supervision.
Strong problem-solving, communication, and stakeholder collaboration skills in a fast-paced global environment.
Demonstrated focus on automation, scalability, maintainability, and measurable business value.
Power BI, semantic modeling, or analytics enablement.
Jira, Azure DevOps, ServiceNow, Control-M, or equivalent engineering and delivery tools.
AI-assisted development, agentic workflows, and modern data product architectures.
Commercial, customer, quality, field-service, or operational reporting data products.
Duration: 4 months with potential to extend into 2027.
Capacity: Full-time, approximately 40 hours per week
Location: One consultant in the United States (U.S. citizenship required) and one consultant in India
Working Model: Regular overlap with US business hours for Agile ceremonies, design reviews, and stakeholder collaboration
Seeking a hands-on Senior Data Engineer Consultant to rapidly design, build, and deploy scalable enterprise data products. The successful consultant will combine strong technical depth with a bias for action, end-to-end ownership, and disciplined delivery.
Design, develop, test, review and support enterprise data pipelines using Snowflake, Azure Data Factory, Azure Data Lake Storage, SQL, and Python.
Build and optimize bronze, silver, and gold data products using scalable ETL/ELT, data modeling, orchestration, and data quality practices.
Translate business requirements into production-ready technical solutions, delivering from design through deployment and support.
Implement automated testing, CI/CD, DevSecOps, DataOps, monitoring, audit controls, and pipeline observability.
Troubleshoot UAT and Production issues, perform root-cause analysis, and implement sustainable fixes.
Create reusable engineering patterns and clear technical documentation; collaborate effectively in Agile teams with architects, product owners, engineers, and business stakeholders.
Comfortable using AI to develop using specs - design, code, build and review production grade pipelines.
Snowflake; Azure Data Factory; Azure Data Lake Storage
Advanced SQL; Python; ETL/ELT; pipeline orchestration
Data warehousing; dimensional modeling; medallion architecture
Performance tuning; data quality; observability; production support
Git; CI/CD; automated testing; Agile delivery
10+ years of hands-on data engineering experience delivering production-grade pipelines and enterprise data products.
Proven ability to work independently, manage technical risks and dependencies, and deliver committed outcomes with minimal supervision.
Strong problem-solving, communication, and stakeholder collaboration skills in a fast-paced global environment.
Demonstrated focus on automation, scalability, maintainability, and measurable business value.
Power BI, semantic modeling, or analytics enablement.
Jira, Azure DevOps, ServiceNow, Control-M, or equivalent engineering and delivery tools.
AI-assisted development, agentic workflows, and modern data product architectures.
Commercial, customer, quality, field-service, or operational reporting data products.
Duration: 4 months with potential to extend into 2027.
Capacity: Full-time, approximately 40 hours per week
Location: One consultant in the United States (U.S. citizenship required) and one consultant in India
Working Model: Regular overlap with US business hours for Agile ceremonies, design reviews, and stakeholder collaboration
Seeking a hands-on Senior Data Engineer Consultant to rapidly design, build, and deploy scalable enterprise data products. The successful consultant will combine strong technical depth with a bias for action, end-to-end ownership, and disciplined delivery.
Design, develop, test, review and support enterprise data pipelines using Snowflake, Azure Data Factory, Azure Data Lake Storage, SQL, and Python.
Build and optimize bronze, silver, and gold data products using scalable ETL/ELT, data modeling, orchestration, and data quality practices.
Translate business requirements into production-ready technical solutions, delivering from design through deployment and support.
Implement automated testing, CI/CD, DevSecOps, DataOps, monitoring, audit controls, and pipeline observability.
Troubleshoot UAT and Production issues, perform root-cause analysis, and implement sustainable fixes.
Create reusable engineering patterns and clear technical documentation; collaborate effectively in Agile teams with architects, product owners, engineers, and business stakeholders.
Comfortable using AI to develop using specs - design, code, build and review production grade pipelines.
Snowflake; Azure Data Factory; Azure Data Lake Storage
Advanced SQL; Python; ETL/ELT; pipeline orchestration
Data warehousing; dimensional modeling; medallion architecture
Performance tuning; data quality; observability; production support
Git; CI/CD; automated testing; Agile delivery
10+ years of hands-on data engineering experience delivering production-grade pipelines and enterprise data products.
Proven ability to work independently, manage technical risks and dependencies, and deliver committed outcomes with minimal supervision.
Strong problem-solving, communication, and stakeholder collaboration skills in a fast-paced global environment.
Demonstrated focus on automation, scalability, maintainability, and measurable business value.
Power BI, semantic modeling, or analytics enablement.
Jira, Azure DevOps, ServiceNow, Control-M, or equivalent engineering and delivery tools.
AI-assisted development, agentic workflows, and modern data product architectures.
Commercial, customer, quality, field-service, or operational reporting data products.
Duration: 4 months with potential to extend into 2027.
Capacity: Full-time, approximately 40 hours per week
Location: One consultant in the United States (U.S. citizenship required) and one consultant in India
Working Model: Regular overlap with US business hours for Agile ceremonies, design reviews, and stakeholder collaboration
HCLTech is a global technology company, home to more than 226,600 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending September 2025 totaled $14.2 billion. To learn how we can supercharge progress for you, visit hcltech.com.
