Technical Lead - Data Engineer (Data&AI)

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Description

Lead Data Engineer Overview We are looking for a Lead Data Engineer who combines hands-on multi-platform expertise with strong leadership in data architecture, pipelines, and CI/CD. This role requires a versatile engineer with deep technical skills across modern data platforms (such as Databricks, Snowflake, AWS, and Azure), an understanding of MLOps/DevOps practices, and the ability to guide a high-performing team in building scalable, production-ready data solutions. You will not be limited to a single platform but will leverage a diverse toolkit to solve complex data challenges. Key Responsibilities · Pipeline & Architecture: Lead hands-on development of scalable ETL/ELT pipelines, data models, and integration frameworks to process high-volume (billions of records) structured and unstructured retail data. · Multi-Platform Engineering: Design, develop, and optimize data processing applications across multiple platforms, including Databricks (Spark/Delta Lake), Snowflake, AWS, or Azure. · Data Integration & Orchestration: Build and manage robust data pipelines using Apache Airflow for orchestration and Airbyte for seamless data integration and movement. · Data Processing: Architect and implement robust solutions for Change Data Capture (CDC), large-scale batch processing, and low-latency real-time/streaming data processing. · API Management: Work extensively with external APIs for data ingestion, as well as design, create, and manage internal REST APIs to serve data

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