Azure Data Engineer

Hiring Now | Azure Data Engineer

(0–2 Years Experience) | Freshers & Experienced Candidates Welcome, Kickstart your career in Azure Data Engineer with us! Job Title: Azure Data Engineer

(0–2 Years Experience) Shift: 07:30 AM – 03:30 PM IST Work Mode: Remote Location: Open to candidates across India Company Description thinkMind Tech is a global technology solutions provider specializing in delivering end-to-end software development services across industries. Leveraging deep engineering expertise and AI-driven, cloud-native architectures, the company builds scalable and secure digital platforms that enable business growth. With capabilities encompassing web, mobile, cloud, enterprise, SaaS, and product engineering, thinkMind Tech integrates cutting-edge technologies for intelligent automation and data-driven ecosystems. Known for combining the agility of a startup with the reliability of an established partner, thinkMind Tech employs modern technologies and advanced methodologies, such as Generative AI accelerators, DevOps, and real-time data ecosystems, to drive innovation and deliver sustainable software solutions. About the Role We are looking for a highly skilled Azure Data Engineer with deep expertise in the Microsoft Azure cloud ecosystem to design, build, and maintain scalable, secure, and high-performance data solutions. This is a full-time remote position focused on developing enterprise-grade ETL/ELT pipelines, data warehousing solutions, and advanced analytics platforms. The ideal candidate will have strong hands-on experience with Azure Data Factory, Azure Databricks, Snowflake, and DBT, along with solid programming expertise in Python, PySpark, and SQL. Role Description As an Azure Data Engineer, you will: Design, build, and maintain scalable data solutions on the Microsoft Azure cloud platform Develop and optimize ETL/ELT pipelines using Azure Data Factory (ADF) Build data transformation workflows using Azure Databricks (PySpark) and DBT Perform data modeling and implement scalable data architectures Manage and optimize data warehousing solutions using Snowflake Support data analytics initiatives by ensuring high-quality, accessible, and reliable datasets Write efficient and optimized SQL queries for complex transformations Ingest and integrate data from multiple structured and unstructured sources Monitor, troubleshoot, and optimize pipelines for performance and reliability Maintain data quality, governance, security, and documentation standards Collaborate with analysts, architects, DevOps teams, and stakeholders in a remote environment

Must-Have Skills Strong experience with Azure Cloud Platform services Proven expertise in Azure Data Factory (ADF) Hands-on experience with Azure Databricks Proficiency in SQL Experience with Snowflake and SnowSQL Practical knowledge of DBT (Data Build Tool) Experience handling large-scale datasets in cloud-based environments Experience in ingesting data from multiple structured and unstructured data sources

Good-to-Have Skills Experience with DataStage, Netezza, Azure Data Lake, Azure Synapse, or Azure Functions Knowledge of Python / PySpark for data transformation Understanding of CI/CD pipelines and DevOps practices Exposure to data governance, metadata management, or data catalog tools Familiarity with BI tools such as Power BI or Tableau Data warehousing experience

Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, or a related field 0-2+ years of experience in data engineering using Azure and Snowflake Strong analytical thinking and problem-solving skills Ability to work effectively in remote, cross-functional teams Azure Data Engineering certifications are a plus

Why Join thinkMind? Work in a cutting-edge, cloud-first environment focused on Azure-based data solutions. Design and build enterprise-scale data platforms that power real business decisions. Gain hands-on experience with modern technologies like Azure Data Factory, Databricks, Snowflake, and DBT. Collaborate with experienced data architects, analysts, and DevOps teams in a fully remote setup. Accelerate your career growth with exposure to large-scale cloud data engineering projects.