Job
Description
Key Responsibilities: Work with presales and business development team during discovery phase, contribute to proposals and RFP responses. Consultative approach to advice clients on AI journey including data strategies, AI/LLM enabled use cases, data platform adoptions. Build and mentor team of data engineers, analysts, ML, ML-Ops engineers. Work with L&D team to build Data & AI competency and enable team to stay current on advancements in technology and business outlook. Architect solution leveraging modern data stack including data platforms (Databricks, Snowflake) and cloud services (Azure, GCP, AWS) Guide end-to-end solutions including data architecture, data pipeline, data governance, security, ML-Ops Requirements 10-12 years of experience in data engineering, analytics, or AI/ML, with at least 3+ years in a leadership role. Hands-on experience with tools like Python, Spark, SQL, Airflow, Kafka, and cloud-native data services. Strong technical knowledge in building modern data platforms, pipelines, and machine learning solutions Deep understanding of AI/ML lifecycle, model management, and MLOps practices. Excellent communication and stakeholder management skills. Expertise/certification in data platofrms like Databricks or Snowflake is a plus
