Data Engineer

Position: Azure Data Engineer Location: Washington, DC 20433 (Hybrid – 4 days onsite per week from Day 1; expected to transition to 100% onsite) Duration: 3 Months (Contract) Job Description: We are seeking an experienced Azure Data Engineer to support the K360 (Knowledge 360) initiative in building a strong and scalable data foundation. This role will focus on designing and implementing modern data pipelines that support both structured and unstructured data, enabling advanced analytics and AI-driven capabilities across the organization. The ideal candidate will have hands-on experience with Azure-based data platforms, modern data transformation tools, and large-scale data processing frameworks. This position will play a key role in establishing the core data infrastructure that powers downstream AI and analytics initiatives. Key Responsibilities • Design, develop, and maintain scalable data pipelines using Azure Data Factory (ADF). • Build and manage data transformation workflows using DBT (Data Build Tool). • Develop and optimize data processing solutions using Databricks and Python. • Integrate and manage both structured and unstructured data sources within the data platform. • Collaborate with data scientists, analysts, and business teams to deliver reliable and high-quality datasets. • Implement best practices for data modeling, data quality, and data governance. • Optimize data workflows for performance, scalability, and cost efficiency. • Support the development of a modern data architecture that enables advanced analytics and AI acceleration. • Troubleshoot and resolve data pipeline issues while ensuring high availability and reliability. Required Skills & Experience • Strong experience in Azure Data Engineering and modern cloud data platforms. • Hands-on experience with Azure Data Factory (ADF) for building and orchestrating data pipelines. • Experience with DBT (Data Build Tool) for data transformation and modeling. • Proficiency in Databricks for large-scale data processing. • Strong programming experience with Python for data engineering tasks. • Experience working with both structured and unstructured data. • Knowledge of data warehousing, ETL/ELT processes, and data modeling. • Familiarity with building scalable data platforms that support analytics and AI workloads. Preferred Qualifications • Experience working on modern data lake or lakehouse architectures. • Familiarity with AI/ML data pipelines and data preparation for machine learning. • Experience working in large enterprise or global data environments. • Knowledge of data governance and data quality frameworks. “Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”