Job description

Job Title: Azure Data Tech Lead Location: Alpharetta, Georgia "Core Skills: Azure, Databricks, ADLS, Spark (Python), SQL, ETL, Delta Lake, PostgreSQL, Data Architecture, Batch & Real-time Processing, Data Modelling Overview We are looking for an experienced Senior/Lead Data Engineer with expertise in designing and delivering scalable, high-performing data solutions on the Azure ecosystem. The ideal candidate will have deep hands-on experience with Databricks, Spark, modern data lakehouse architectures, data modelling, and both batch and real-time data processing. You will be responsible for driving end-to-end data engineering initiatives, influencing architectural decisions, and ensuring robust, high-quality data pipelines. Key Responsibilities • Architect, design, and implement scalable data platforms and pipelines on Azure and Databricks. • Build and optimize data ingestion, transformation, and processing workflows across batch and real-time data streams. • Work extensively with ADLS, Delta Lake, and Spark (Python) for large-scale data engineering. • Lead the development of complex ETL/ELT pipelines, ensuring high quality, reliability, and performance. • Design and implement data models, including conceptual, logical, and physical models for analytics and operational workloads. • Work with relational and lakehouse systems including PostgreSQL and Delta Lake. • Define and enforce best practices in data governance, data quality, security, and architecture. • Collaborate with architects, data scientists, analysts, and business teams to translate requirements into technical solutions. • Troubleshoot production issues, optimize performance, and support continuous improvement of the data platform. • Mentor junior engineers and contribute to building engineering standards and reusable components. Required Skills & Experience • Hands-on data engineering experience in enterprise environments. • Strong expertise in Azure services, especially Azure Databricks, Functions, and Azure Data Factory (preferred). • Advanced proficiency in Apache Spark with Python (PySpark). • Strong command over SQL, query optimization, and performance tuning. • Deep understanding of ETL/ELT methodologies, data pipelines, and scheduling/orchestration. • Hands-on experience with Delta Lake (ACID transactions, optimization, schema evolution). • Strong experience in data modelling (normalized, dimensional, lakehouse modelling). • Experience in both batch processing and real-time/streaming data (Kafka, Event Hub, or similar). • Solid understanding of data architecture principles, distributed systems, and cloud-native design patterns. • Ability to design end-to-end solutions, evaluate trade-offs, and recommend best-fit architectures. • Strong analytical, problem-solving, and communication skills. • Ability to collaborate with cross-functional teams and lead technical discussions. Preferred Skills • Experience with CI/CD tools such as Azure DevOps and Git. • Familiarity with IaC tools (Terraform, ARM). • Exposure to data governance and cataloging tools (Azure Purview). • Experience supporting machine learning or BI workloads on Databricks."

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