Lead Data Engineer / Data Architect

We are seeking an experienced Lead Data Engineer / Data Architect to design, scale, and optimize enterprise-grade Lakehouse data platforms. The ideal candidate will have deep expertise in Databricks, Apache Spark, Delta Lake, cloud data platforms, and enterprise data architecture, with proven experience building production-grade scalable data ecosystems.

This role requires a strong technical leader who can drive architecture decisions, establish data engineering standards, optimize platform performance and cost, and mentor engineering teams., * Design and lead enterprise Lakehouse architecture implementation using Databricks

• Build scalable, secure, and production-ready data platforms
• Architect and optimize large-scale data pipelines and transformation frameworks
• Drive engineering standards, architecture governance, and best practices
• Optimize Spark / Databricks performance, scalability, and cost efficiency
• Design and implement Delta Lake-based data architectures
• Define and enforce Medallion architecture data modeling standards
• Collaborate with business, analytics, engineering, and architecture stakeholders
• Mentor and guide data engineering teams
• Support platform modernization and cloud data transformation initiatives
• Troubleshoot production issues and optimize platform reliability

• 8+ years of Data Engineering / Data Platform Engineering experience
• Proven experience in enterprise data architecture and large-scale data platform design
• Strong leadership experience guiding engineering teams and architecture decisions
• Hands-on experience building production-grade data platforms

Must Have Technical Skills

Databricks / Big Data Engineering

Strong hands-on expertise with:

• Databricks
• Apache Spark
• PySpark
• Scala
• Delta Lake
• Lakehouse Architecture
• Distributed data processing
• Large-scale ETL / ELT pipelines

Data Architecture

Strong experience in:

• Enterprise data platform architecture
• Scalable data pipeline design
• Data platform modernization
• Lakehouse implementation
• Performance optimization
• Cost optimization
• Production data platform engineering

Data Modeling

Strong understanding of:

• Medallion Architecture

• Bronze Layer
• Silver Layer
• Gold Layer

• Data warehousing concepts
• Dimensional modeling
• Data governance principles
• Metadata-driven architecture

Cloud Platforms

Hands-on experience with one or more:

• AWS
• Azure
• Google Cloud Platform

Database / Query Optimization

Strong expertise in:

• SQL
• Query optimization
• Large-scale data transformations
• Data performance tuning
• Partitioning / indexing strategies
• Compute optimization

Engineering / DevOps

Experience with:

• CI/CD pipelines for data engineering
• Version control (Git)
• Deployment automation
• Monitoring / observability
• Production support best practices, * Experience in enterprise-scale data modernization programs
• Architecture leadership experience
• Exposure to data governance and security frameworks
• Experience with streaming data platforms is a plus