Lead Data Engineer

Responsibilities

• Lead the design, development, and optimization of scalable data pipelines supporting ingestion, transformation, and enterprise-wide data consumption.
• Architect and implement enterprise-grade ETL/ELT frameworks using Azure Fabric or comparable cloud data platforms.
• Oversee and optimize data integrations from ERP (NetSuite/SAP), CRM (Salesforce), internal systems, APIs, and third-party data sources.
• Design and govern high-quality, scalable data models supporting analytics, reporting, operational systems, and advanced use cases.
• Partner with Data Architects to define and implement Lakehouse patterns, Delta Lake strategies, medallion architecture, and domain-driven design principles.
• Establish and enforce data quality frameworks, validation standards, lineage tracking, and observability practices.
• Drive performance optimization, scalability, reliability, and cost governance across cloud environments.
• Provide technical leadership and mentorship to data engineers; conduct design reviews and enforce engineering best practices.
• Collaborate cross-functionally with analysts, application teams, and business stakeholders to translate requirements into scalable data solutions.
• Lead MDM, metadata management, governance, and data standardization initiatives.
• Evaluate emerging technologies and recommend platform improvements aligned with enterprise strategy.

Requirements

• 10+ years of experience in data engineering, data architecture, or related roles.
• Proven experience leading large-scale data platform initiatives in cloud environments.
• Extensive hands-on experience with Azure data services (Data Lake, Data Factory, Fabric, Synapse, or similar).
• Advanced proficiency in SQL and Python; experience with Spark or distributed processing frameworks.
• Deep experience designing and implementing enterprise ETL/ELT frameworks.
• Strong expertise in data modeling (dimensional modeling, star schema, lakehouse/Delta modeling).
• Experience integrating complex enterprise systems (ERP, CRM, operational platforms).
• Strong understanding of data governance, metadata management, MDM, and data quality frameworks.
• Experience with performance tuning, workload optimization, and cloud cost management.
• Demonstrated ability to lead technical teams, conduct architecture reviews, and mentor engineers.
• Strong problem-solving, debugging, and system design skills.
• Travel may be required up to 5%, depending on business needs.

Qualifications

• Minimum Qualifications: 10+ years of experience in data engineering, data architecture, or related roles.
• Proven experience leading large-scale data platform initiatives in cloud environments.
• Extensive hands-on experience with Azure data services (Data Lake, Data Factory, Fabric, Synapse, or similar).
• Advanced proficiency in SQL and Python; experience with Spark or distributed processing frameworks.
• Deep experience designing and implementing enterprise ETL/ELT frameworks.
• Strong expertise in data modeling (dimensional modeling, star schema, lakehouse/Delta modeling).
• Experience integrating complex enterprise systems (ERP, CRM, operational platforms).
• Strong understanding of data governance, metadata management, MDM, and data quality frameworks.
• Experience with performance tuning, workload optimization, and cloud cost management.
• Demonstrated ability to lead technical teams, conduct architecture reviews, and mentor engineers.
• Strong problem-solving, debugging, and system design skills.
• Preferred Qualifications: Experience with Delta Tables, Snowflake, Synapse, or comparable cloud data platforms.
• Familiarity with finance, operations, energy, or ERP-driven data domains.
• Experience designing API-based data integrations and modern integration patterns.
• Azure certifications (Data Engineer Associate, Solutions Architect, or equivalent).
• Experience enabling analytics teams, data science workflows, or ML pipelines.
• Experience implementing enterprise data security and compliance frameworks.

Use of AI Tools

As a technology organization, Qcells expects team members to leverage AI models and AI-assisted tools in their daily workflows where appropriate. Candidates should be comfortable working in an AI-augmented environment and apply sound judgment when using AI-generated outputs.

Physical, Mental & Environmental Demands

To comply with the Rehabilitation Act of 1973, the essential physical, mental, and environmental requirements for this job are listed below. These are requirements normally expected to perform regular job duties. Incumbent must be able to successfully perform all of the functions of the job with or without reasonable accommodation. Mobility: Standing 20%, Sitting 70%, Walking 10%, Lifting up to 10 Pounds, Pushing up to 10 Pounds, Pulling up to 10 Pounds. Strength: Pulling up to 10 Pounds, Pushing up to 10 Pounds, Carrying up to 10 Pounds. Dexterity: Typing Frequently, Handling Frequently, Reaching Frequently. Agility: Turning Occasionally, Twisting Occasionally, Bending Occasionally, Crouching Occasionally, Balancing Never, Twisting Never, Bending Never, Crouching Never, Climbing Never, Crawling Never, Kneeling Never.

Schedule

Not specified.

Benefits

Not specified.

Pay

Not specified.