Data Engineer

About Accelyst is an innovative AI consultancy that leverages a unique catalog of industry-specific AI agents and leading-edge platforms to deliver secure, scalable, and ROI-optimized solutions. We combine deep industry knowledge with advanced technical expertise to rapidly deploy AI-driven capabilities that augment and automate workflows for employees, customers, prospects, and investors. Why Accelyst? Join Accelyst to be part of a dynamic team that leverages AI-driven technology to make a positive impact. Our leadership, with Big Four Consulting experience, fosters a nimble, client-focused environment, minimizing bureaucracy to enhance delivery and professional growth. You’ll work on complex AI-powered products that challenge and inspire, while benefiting from our profit-sharing model that reflects our commitment to respect, ownership, and integrity. Job Description: Job Title: Data Engineer Experience: 10+ Years Work Hours - EST We are seeking an experienced Data Engineer with strong expertise in migrating large-scale data platforms from On-Premises environments to Azure Cloud. The ideal candidate will have hands-on experience designing and implementing data pipelines using Azure Data Lake, Azure Databricks, and Azure Data Factory, ensuring secure, scalable, and high-performance data solutions. Key Responsibilities Lead and execute data migration from On-Premises systems to Azure Cloud with minimal downtime and high data integrity. Design, build, and maintain scalable data pipelines using Azure Data Factory (ADF) for batch and incremental data loads. Implement data storage and processing solutions using Azure Data Lake (ADLS Gen2). Develop and optimize ETL/ELT workflows using Azure Databricks (PySpark/SQL) for large datasets. Ensure data quality, validation, and reconciliation during and after migration. Collaborate with stakeholders, architects, and analytics teams to understand data requirements and deliver cloud-native solutions. Monitor, troubleshoot, and optimize performance of Azure data pipelines and workloads. Follow best practices for security, governance, and cost optimization in Azure. Required Skills • Strong experience in On-Premises to Azure Cloud data migration • Hands-on expertise with Azure Data Lake (ADLS) • Strong working knowledge of Azure Databricks (PySpark, Spark SQL) • Experience building pipelines using Azure Data Factory • Good understanding of data warehousing, ETL/ELT concepts, and data modeling • Proficiency in SQL and data transformation techniques Nice to Have • Experience with Azure DevOps CI/CD for data pipelines • Knowledge of Azure security, RBAC, and data governance • Exposure to Power BI or other analytics tools