Lead Data Engineer

Overview

• Lead end-to-end architecture, design, and implementation of complex cloud-based data pipelines.
• Translate business requirements into scalable and reliable technical data solutions in collaboration with architects and stakeholders.
• Ensure high availability, performance, scalability, and security of enterprise data systems.
• Define and enforce best practices for data modeling, transformation, governance, and DevOps.
• Architect and optimize ingestion, transformation, and storage frameworks for performance and cost efficiency.
• Implement Infrastructure as Code (IaC) using tools such as Terraform or ARM templates.
• Design and manage CI/CD pipelines for automated deployment and testing of data workflows.
• Provide technical leadership, mentorship, and code reviews for data engineering teams.
• Participate in enterprise data architecture design and review discussions.
• Ensure data governance, lineage, observability, and compliance standards are maintained.
  
  

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 10+ years of overall IT experience with at least 7+ years in Data Engineering.
• Strong hands-on expertise in:
• Python
• SQL
• Apache Spark
• Azure Data Services (ADF, Synapse, Data Lake, Azure Fabric)
• Working knowledge of AWS data services.
• Experience designing and implementing:
• Data Lake, Delta Lake, and Lakehouse architectures
• Big Data processing systems
• Proficiency in at least one relational database (PostgreSQL, Redshift, Snowflake) and exposure to NoSQL databases (MongoDB, Cosmos DB, etc.).
• Experience implementing Infrastructure as Code (Terraform preferred).
• Strong understanding of CI/CD frameworks and DevOps practices.
• Proven ability to build scalable, fault-tolerant, and cost-optimized data pipelines.
  

• Cloud certifications (Azure / AWS / GCP).
• Experience with Databricks, Snowflake, or Terraform.
• Familiarity with data governance, lineage, and observability tools.
• Exposure to Microsoft Fabric ecosystem.
• Strong stakeholder communication and cross-functional collaboration skills.
• Demonstrated leadership in managing and mentoring engineering teams.
  
  

• Opportunity to lead large-scale, enterprise cloud data transformations.
• Flexible Hybrid / Remote work model.
• Competitive compensation with negotiation flexibility for exceptional talent.
• Collaborative and innovation-driven work culture.