About the job

About AllCloudAllCloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, AllCloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation.AllCloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, AllCloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth.AllCloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io

Job SummaryWe are looking for a talented and experienced Data Engineer with a passion for data and cloud technologies to join our team. In this role, you will be a key player in designing, developing, and maintaining our AWS and Databricks-based data platform. You will bridge the gap between robust Data Engineering, Database Administration (DBA), and high-performance Analytics Engineering.The ideal candidate understands the Lakehouse architecture, has experience managing modern cloud data warehouses like Snowflake, and possesses the ability to build scalable ETL pipelines that drive data-driven business decisions.

• Key ResponsibilitiesEnd-to-End Pipelines: Develop and maintain complex ETL/ELT pipelines using Python/PySpark on the Databricks platform, as well as loading and transforming data within Snowflake.
• Data Architecture: Implement and manage data layers following the Medallion architecture (Bronze, Silver, Gold) using Delta Lake.
• Optimization & Analytics: Set up and manage Databricks SQL Warehouses, perform query optimization, and utilize internal visualizations for rapid data exploration.
• Cloud Infrastructure: Leverage AWS cloud services to manage data storage, compute resources, and secure data movement.
• DBA & Performance Tuning: Act as a custodian for our data platform—managing indexing, clustering, vacuuming, and performance tuning across both Delta Lake and relational/warehouse environments to ensure cost-efficiency and high speed.
• Data Modeling: Design data models (Star Schema / Snowflake) in the Gold layer to ensure optimal performance for BI tools (e.g., Power BI, Tableau).
• Data Governance: Manage metadata, permissions, and lineage using Unity Catalog and platform-specific access controls.
• Quality Control: Implement automated Data Quality tests as an integral part of the CI/CD data pipelines.