Senior Data Engineer - (100% Remote)
- Fully Remote : Work from anywhere with flexible hours that fit your lifestyle.
- Award-Winning Culture : Be part of a company recognized for exceptional employee satisfaction, inclusivity, and professional development.
- Competitive Compensation : Generous salary, performance bonuses, and comprehensive benefits package.
- Professional Growth : Access to mentorship programs, certifications, and opportunities to advance your career.
- Cutting-Edge Tech : Work with state-of-the-art tools and technologies on impactful, high-visibility projects.
Key Responsibilities :
Design and implement scalable, efficient data pipelines using Azure Data Lake , Databricks , Snowflake , and Synapse Analytics .Develop and optimize workflows with Apache Spark and Scala for batch and streaming data processing.Build, maintain, and enhance robust ETL / ELT pipelines tailored to big data applications within Azure ecosystems.Manage and optimize data storage solutions like Azure Data Lake Storage , Snowflake , and Synapse Analytics to ensure peak performance and cost-efficiency.Partner with data scientists, analysts, and business teams to ensure the reliability and availability of data platforms.Monitor and fine-tune the performance of data platforms in production environments.Enforce best practices for data governance, security, and compliance in Azure-based data frameworks.Stay ahead of the curve by researching and integrating new big data technologies to enhance scalability and performance.Requirements :
Essential Skills and Experience :
A minimum of 5 years of experience in data engineering or related fields.At least 3 years of hands-on expertise in Apache Spark using Scala .Advanced knowledge of Azure data services , including Azure Data Lake , Azure Databricks , Azure Synapse Analytics , and Azure Data Factory .Proficiency with Snowflake , including schema design, performance optimization, and integration with cloud platforms.Solid expertise in cloud-based big data solutions , particularly within the Azure ecosystem.Strong knowledge of data modeling , ETL / ELT pipelines , and database concepts .Experience with streaming platforms such as Spark Streaming , Kafka , or Event Hubs .Familiarity with data lake and data warehouse architecture (e.g., Delta Lake , Snowflake , Synapse ).Proficiency in DevOps practices, including CI / CD pipelines for data engineering workflows.Preferred Skills :
Knowledge of Python for data engineering tasks.Experience with Azure Machine Learning or other machine learning platforms integrated with data workflows.