Senior Technical Lead

HCL America Inc.
Brown, WV, United States
15 days ago
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Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Compensation
$148,000.0
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Artificial Intelligence JIRA Automation of Tests Microsoft Azure Continuous Integration Information Engineering Extract Transform Load (ETL) Data Warehousing Dimensional Modeling Python (Programming Language) Performance Tuning
+12 more
Power BI DataOps Azure Data Lake SQL Databases Azure Data Factory Sql Optimization Snowflake Git Data Pipelines Devsecops Servicenow Control M

Job description

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.

Core Responsibilities 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.

Required Technical Skills

Platforms

Snowflake; Azure Data Factory; Azure Data Lake Storage

Engineering

Advanced SQL; Python; ETL/ELT; pipeline orchestration

Architecture

Data warehousing; dimensional modeling; medallion architecture

Requirements

Performance tuning; data quality; observability; production support

Delivery

Git; CI/CD; automated testing; Agile delivery

Experience and Delivery Profile 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. Preferred Experience 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. Engagement Details

Benefits & conditions

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, 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

Skill Requirements Other Requirements Maximum Salary (US): 148000 Minimum Salary (US): 100000 #body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-

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