Senior Data Engineer - Databricks
Posted Updated
Requirements
(Mandatory
) 10+ years in data industry performing solutioning, architecting and engineering tasks. 3+ years on databricks solution implementation. Proven consulting/services experience and ability to present solutions to senior client stakeholders. Hands‑on experience in leading a large data platform implementations Deep expertise in Databricks with lakehouse architectures, MLflow, Delta Lake. Strong cloud concepts and architecture knowledge (AWS). Data modelling, Spark, SQL, ETL/ELT, and orchestration tools. Understanding of data governance with Unity Catalog, security, and modern data platform design. Requirements
(Nice to have) Knowledge of AI/ML requirements and the ability to work with AI/ML experts. Pre‑sales experience including Use case definition, POC creation and RFP responses. Knowledge of MLOps, data observability, DevOps/CI-CD, and BI tools. Databricks or AWS certifications. Excellent communication, client‑facing abilities, and solution articulation. Hands‑on, consultative, and able to lead teams and delivery. Job Responsibilities Lead end‑to‑end data platform implementations on Databricks, ensuring scalable and high‑quality delivery. Align data architecture with AI/ML initiatives and guide clients on data readiness for AI. Mentor and develop data engineering and architecture teams. Contribute to internal Solution Review Board with the best practices, reference architectures, and reusable assets
(Mandatory
) 10+ years in data industry performing solutioning, architecting and engineering tasks. 3+ years on databricks solution implementation. Proven consulting/services experience and ability to present solutions to senior client stakeholders. Hands‑on experience in leading a large data platform implementations Deep expertise in Databricks with lakehouse architectures, MLflow, Delta Lake. Strong cloud concepts and architecture knowledge (AWS). Data modelling, Spark, SQL, ETL/ELT, and orchestration tools. Understanding of data governance with Unity Catalog, security, and modern data platform design. Requirements
(Nice to have) Knowledge of AI/ML requirements and the ability to work with AI/ML experts. Pre‑sales experience including Use case definition, POC creation and RFP responses. Knowledge of MLOps, data observability, DevOps/CI-CD, and BI tools. Databricks or AWS certifications. Excellent communication, client‑facing abilities, and solution articulation. Hands‑on, consultative, and able to lead teams and delivery. Job Responsibilities Lead end‑to‑end data platform implementations on Databricks, ensuring scalable and high‑quality delivery. Align data architecture with AI/ML initiatives and guide clients on data readiness for AI. Mentor and develop data engineering and architecture teams. Contribute to internal Solution Review Board with the best practices, reference architectures, and reusable assets