Senior Data Engineer - Lead

We are seeking a Senior Data Engineer - Lead to serve as both a technical leader and team mentor across client-facing data initiatives. This role combines hands-on architecture and engineering responsibilities with delivery leadership, team mentorship, and limited people-management responsibilities.

You will architect and implement modern data platforms, guide engineering teams, collaborate closely with BI, software, and AI specialists, and serve as a trusted advisor to clients. You will be expected to lead the end-to-end data engineering lifecycle—from platform architecture and data integration through governance, analytics enablement, and production delivery.

This role is ideal for someone who enjoys balancing technical excellence, client engagement, and team leadership while remaining hands-on with modern cloud and data technologies.

Responsibilities

Technical Leadership & Architecture

• Serve as technical lead on client engagements, driving architecture, implementation, and delivery decisions
• Architect modern data platforms using Databricks and related cloud technologies, with experience in Microsoft Fabric, Snowflake, Azure, or similar platforms considered highly valuable.
• Define scalable, secure, and maintainable data architectures that support analytics, reporting, machine learning, and AI initiatives
• Lead infrastructure design, CI/CD implementation, Infrastructure-as-Code, and deployment automation
• Evaluate architectural tradeoffs and recommend solutions aligned to client goals and long-term scalability
• Establish engineering standards, best practices, and reusable design patterns across projects

Data Engineering & Development

• Design and build enterprise-grade ETL/ELT pipelines and data integration solutions
• Develop solutions utilizing Databricks, Microsoft Fabric, Azure Data Factory, Snowflake, DBT, Spark, PySpark, Python, and SQL
• Optimize batch, streaming, and near-real-time data processing workloads
• Implement data quality, lineage, governance, observability, and monitoring frameworks
• Design semantic models and curated data products for BI, analytics, and AI consumption
• Support implementation of modern lakehouse and data warehouse architectures

Team Leadership & Mentorship

• Provide technical leadership and mentorship to Data Engineers across multiple projects
• Participate in interviewing, onboarding, and development of engineering team members
• Conduct code reviews and promote engineering best practices
• Help guide career growth, technical development, and knowledge sharing within the team
• Support resource planning and engineering capacity discussions with leadership
• Foster a culture of accountability, collaboration, and continuous improvement

Project Planning & Delivery

• Break down client requirements into actionable engineering workstreams
• Contribute to pre-sales scoping and estimation, ensuring effort estimates are technically defensible before commitments are made
• Drive backlog creation, refinement, estimation, and sprint planning activities
• Identify technical risks, dependencies, and mitigation strategies
• Ensure engineering work is delivered with high quality and within project budgets
• Partner with project leadership to maintain project health and successful client outcomes

Client Engagement & Consulting

• Serve as the primary technical point of contact for assigned client accounts, maintaining the client's technical confidence and owning the relationship from kickoff through project close
• Lead technical discovery workshops, architecture reviews, and solution design sessions
• Present recommendations to both technical and business stakeholders
• Translate complex technical concepts into business-focused outcomes
• Contribute to project estimation, solution design, and Statement of Work development
• Identify opportunities for future phases and expanded client value

What We're Looking For

Required Qualifications

• 8+ years of data engineering experience with at least 2–3 years serving as a technical lead or team lead
• Strong experience with Microsoft Fabric, Databricks, Snowflake, and modern cloud data platforms
• Advanced proficiency in SQL and Python
• Experience building scalable ETL/ELT pipelines and enterprise data architectures
• Strong understanding of dimensional modeling, lakehouse architectures, and analytics engineering
• Experience with CI/CD, Infrastructure-as-Code, and cloud-native development practices
• Familiarity with data governance, lineage, metadata management, and security best practices
• Strong client-facing consulting and communication skills
• Experience working in Agile delivery environments

Preferred Qualifications

• Experience with Microsoft Purview, Unity Catalog, Snowflake Horizon, or similar governance platforms
• Experience with Azure cloud architecture, networking, and security, including VNets, private networking, hybrid connectivity, and enterprise-scale data platform deployments.
• Experience supporting machine learning, AI, or advanced analytics initiatives
• Familiarity with Retrieval-Augmented Generation (RAG), vector databases, and AI-ready data architectures
• Experience using AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, or similar technologies
• Experience managing or formally leading engineering teams
• Microsoft, Databricks, Snowflake, or cloud platform certifications