$ cat jobs/senior-data-engineer-kmstechnology1-d76510a1a1d5.json
Senior Data Engineer
At KMS Technology Mexico, we are passionate about building innovative software solutions that drive impact. As part of an international tech company, we offer a collaborative and inclusive environment where your ideas matter and your growth is our priority. We are seeking a highly skilled Senior Data Engineer with strong experience in Databricks and Microsoft Azure to design, develop, and maintain scalable data solutions that support business intelligence, analytics, and operational workloads. This role is responsible for building robust data pipelines, optimizing data processing, and ensuring reliable, high-performance data platforms. You will collaborate with clients, business stakeholders, and cross-functional engineering teams to translate business requirements into scalable technical solutions. This position also involves partnering with distributed teams globally, requiring strong communication and collaboration skills to deliver high-quality data solutions. Responsibilities Design, develop, and maintain scalable data pipelines using Databricks and Azure services. Build and optimize ETL/ELT workflows to support data ingestion, transformation, and delivery. Develop and optimize Apache Spark (PySpark) jobs to efficiently process large-scale datasets. Design and implement scalable data solutions that support analytics, reporting, and operational business needs. Collaborate with business stakeholders and clients to gather requirements and translate them into technical solutions. Ensure data quality, consistency, reliability, and performance across all data processing workflows. Optimize data processing jobs and storage solutions to improve performance and resource utilization. Troubleshoot and resolve issues related to data pipelines, Spark jobs, and Azure data services. Participate in architecture discussions, code reviews, and technical design sessions. Create and maintain technical documentation for data pipelines, data models, and operational processes. Work c
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