Lead Data Engineer – Analytics & AI

Lead technical design and hands-on engineering delivery of enterprise data, analytics, and AI/ML solutions.

Translate high-level architecture into detailed data models, pipelines, and implementation specs used by engineering teams.

Guide and mentor data engineering teams to ensure scalable, maintainable, and production-ready data platforms with focus on reliability and performance.

Significant professional experience in data engineering, data warehousing, or data architecture, including leading technical design or delivery of enterprise data solutions.

Strong hands-on expertise in SQL, data modeling, ETL/ELT, data pipelines, and enterprise data warehouse or lakehouse architectures.

Ability to translate high-level designs into detailed technical designs and lead engineering delivery with code/design reviews and troubleshooting complex integration/scalability/production issues.

Work Experience Required: Significant professional experience in relevant data engineering roles (exact duration not explicitly mentioned).

Experienced technical leader comfortable bridging solution architecture and engineering implementation in complex enterprise data environments.

Strong problem solver who can troubleshoot production and integration issues spanning multiple systems and workloads (batch, CDC, streaming).

Familiar with modern cloud data platforms (e.g., Snowflake, Databricks, Redshift, Azure Synapse), MLOps, and advanced analytics use cases aligned with AI/ML teams.