Senior Data Engineer

About the Project:We are engaging with one of customer to build and operationalize their Enterprise Data Platform (EDP). It is a strategic initiative to mature their data and analytics capabilities across the organization. The project involves building out a robust data platform, establishing a new operating model, and delivering foundational data products. You will be working closely with the customer to fill critical gaps in architecture, governance, security, and data product delivery.What You'll Do:As a Data Engineer on this team, you will be a hands-on contributor across all facets of the project. Your responsibilities will be directly mapped to the customer's needs and gaps, including:Platform Foundations (Reference Architecture & DataOps): Collaborate on the design and implementation of a consolidated EDP reference architecture. You will be responsible for building out and hardening the platform's core components using Azure Synapse , Azure Databricks , and Azure Data Lake Storage (ADLS) . You will help define and implement a DataOps model, including CI/CD pipelines, environments, and observability.Data Governance & Quality: Support the operationalization of a data governance framework. This includes implementing data classification policies, setting up data quality scorecards , and configuring a data catalog with ownership and lineage in a tool like Azure Purview .Data Security & Access: Implement fine-grained access controls using patterns like Row-Level Security and Column-Level Security . You'll help design and apply a security model using Azure Entra ID groups and implement policy-as-code to protect PII.Data Product Pipeline Factory: Build and maintain scalable and repeatable data pipelines to ingest, transform, and publish data from various sources. You will work on creating a standardized framework for data products (from bronze to gold layers), ensuring observability and adherence to quality standards.Data Catalog & Glossary: Configure and populate the enterprise data catalog with metadata and a business glossary. You will be responsible for migrating "priority" datasets and embedding governance checks directly into the SDLC.Data Literacy & Change Management: Contribute to the enablement of data stewards, engineers, and analysts by providing practical, role-based training anchored to the data products you build.What We're Looking For:We are seeking hands-on data engineers with a passion for building robust, well-governed, and secure data platforms. A strong candidate for this team will have:Deep Azure Data Services Expertise: Proven, hands-on experience with the Azure data ecosystem, specifically Azure Synapse Analytics , Azure Databricks , Azure Data Lake Storage (ADLS) , and Azure Purview . Experience with Unity Catalog is highly desirable.Solid experience with Azure data services, including Azure Data Lake Storage (ADLS) and Azure Synapse Analytics .Data Engineering Fundamentals: Strong background in data modeling, ETL/ELT processes, and building scalable data pipelines for batch and streaming data.Programming & Scripting: Proficiency in Python and PySpark is essential for data transformation and pipeline development in Azure Databricks. Strong SQL skills are also required.DevOps & CI/CD: Experience with DataOps principles, including setting up and maintaining CI/CD pipelines using tools like Azure DevOps or GitHub Actions. Familiarity with managing environments and infrastructure as code is a plus.Data Governance & Security: Practical experience or a solid understanding of data governance concepts, including data quality, lineage, metadata management, and access control models ( RBAC/ABAC ).Knowledge of data modeling techniques, data warehousing, and lakehouse architectures.Qualifications:Bachelor's or Master's degree in Computer Science, Engineering, or a related field.5+ years of experience in a data engineering role.Excellent problem-solving, analytical, and communication skills.Demonstrated ability to work effectively in a collaborative and fast-paced environment.