Data Engineer

Valorem Reply is an award-winning digital transformation firm focused on delivering solutions around data-driven enterprise, IT modernization, customer experience, product transformation and digital workplace by leveraging the power of Microsoft technologies.  We provide hyper-scale and agile delivery of unique digital business services, strategic business models and design-led user experiences. Our innovative strategies and solutions securely and rapidly transform the way our clients do business As a Data Engineer, you will design, build, and optimize modern data platforms using Microsoft Azure, Microsoft Fabric, Power BI, and Databricks. You combine deep technical expertise with strong consulting skills to engage clients, understand their business needs, and translate requirements into scalable solutions. You contribute to solution architecture and deliver high-quality data solutions that drive measurable business value. You are comfortable discussing technical details with engineers, facilitating design sessions with clients, and presenting recommendations to leadership. About Reply Reply specializes in the design and implementation of solutions based on new communication channels and digital media. Reply is a network of highly specialized companies supporting global industrial groups operating in the telecom and media, industry and services, banking, insurance and public administration sectors in the definition and development of business models enabled for the new paradigms of AI, cloud computing, digital media and the Internet of Things. Reply services include Consulting, System Integration and Digital Services. Reply is an equal opportunity employer. We are committed to provide equal opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you need assistance and reasonable accommodation due to a disability during the application or the recruiting process, email us at [email protected]. Visit our website at www.reply.com to learn more about our open roles. Responsibilities Work directly with clients to understand business goals, data challenges, and technical requirements. Lead or support discovery sessions, requirements workshops, architecture discussions, and solution reviews. Develop and optimize batch and streaming data ingestion pipelines from enterprise applications, databases, APIs, and file-based sources. Implement medallion/Lakehouse architectures, dimensional models, and data transformation workflows to support analytics and reporting use cases. Engineer solutions using technologies such as PySpark, Spark SQL, SQL, Python, Delta Lake, and orchestration tools within Azure and Databricks. Recommend best practices for data modeling, governance, lineage, monitoring, DevOps, and security. Minimum Requirements Bachelor’s degree in computer science or related field 4 years of experience in data engineering, data platform development, or cloud data solutions 2 years of hands-on experience with Azure Databricks, Apache Spark, or similar distributed data processing technologies Expertise with Microsoft Azure infrastructure and data resources, including Fabric, Azure Data Factory, Synapse Data Analytics ,Power BI, Azure SQL, Azure Cosmos DB Expertise with Databricks, specifically the ability to design enterprise-level strategy and architecture including Unity Catalog, data warehousing, data sharing DevOps for data, GitHub, automated testing, and working with containers (AKS, Docker, registries, etc.) Excellent communication skills, ability to clearly explain concepts to teammates and customers, and quickly learn new concepts and technologies Preferred Qualifications Experience working directly with clients, business stakeholders, or cross-functional teams in a consulting or professional services environment Experience with data management, including data governance, data security, master data management, and familiarity with different industry security requirements Broad experience with data/reporting tools, architectures, cloud vendors, and data/AI concepts other than Microsoft

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