Lead Data Engineer

Job Title : Lead Data Engineer

Work Mode : Remote

Experience : 10+ Years

Notice Period : Immediate / 10 days NP

Key Responsibilities

• Lead and mentor a team of data engineers, architects, and analysts within the Data Program.
• Architect and deliver scalable data platforms leveraging:
• Azure Databricks for data processing
• DBT or Coalesce for data transformation
• Boomi Integration Platform
• PowerApps and Power BI for reporting and analytics
• Design, develop, and deploy data processing solutions aligned with business requirements.
• Collaborate with cross-functional teams (engineers, architects, business analysts) to gather, analyze, and interpret requirements.
• Translate high-level solution designs into detailed technical implementation plans.
• Take ownership of technical delivery, ensuring quality, scalability, and performance.
• Define and manage work breakdown structures (WBS) for ETL, reporting, and analytics tasks.
• Lead Agile ceremonies such as sprint planning, daily stand-ups, and retrospectives.
• Assign, monitor, and track tasks for data engineers and Power BI developers.
• Identify and resolve delivery challenges, acting as a key escalation point.
• Coordinate across multiple vendors and workstreams for seamless project execution.
• Ensure QA, testing, and deployment readiness for data pipelines and reporting layers.
• Track project progress, manage dependencies, and communicate risks and status updates to stakeholders.

Required Skills & Experience

• 10+ years of experience leading data engineering or analytics teams.
• Proven experience in architecting or managing Data Platform solutions using:
• Azure Databricks
• DBT or Coalesce (Data Transformation)
• Boomi (Integration)
• PowerApps and Power BI (Reporting & Visualization)
• Strong understanding of data architecture, data modeling, and ETL design.
• Excellent communication and leadership skills with a collaborative mindset.
• Experience managing multi-disciplinary teams in Agile environments.
• Passion for building scalable, maintainable, and high-performance data solutions.