Job
Description
About Veersa - Veersa Technologies is a US-based IT services and AI enablement company founded in 2020, with a global delivery center in Noida (Sector 142). Founded by industry leaders with an impressive 85% YoY growth A profitable company since inception Team strength: Almost 400 professionals and growing rapidly Our Services Include Digital & Software Solutions: Product Development, Legacy Modernization, Support Data Engineering & AI Analytics: Predictive Analytics, AI/ML Use Cases, Data Visualization Tools & Accelerators: AI/ML-embedded tools that integrate with client systems Tech Portfolio Assessment: TCO analysis, modernization roadmaps, etc. Tech Stack - * AI/ML, IoT, Blockchain, MEAN/MERN stack, Python, GoLang, RoR, Java Spring Boot, Node.js Databases: PostgreSQL, MySQL, MS SQL, Oracle Cloud: AWS & Azure (Serverless Architecture) Website: https://veersatech.com LinkedIn: Feel free to explore our company profile About The Role We are seeking a highly skilled and experienced Data Engineer & Lead Data Engineer to join our growing data team. This role is ideal for professionals with 2 to 10 years of experience in data engineering, with a strong foundation in SQL, Databricks, Spark SQL, PySpark, and BI tools like Power BI or Tableau. As a Data Engineer, you will be responsible for building scalable data pipelines, optimizing data processing workflows, and enabling insightful reporting and analytics across the organization. Key Responsibilities Design and develop robust, scalable data pipelines using PySpark and Databricks. Write efficient SQL and Spark SQL queries for data transformation and analysis. Work closely with BI teams to enable reporting through Power BI or Tableau. Optimize performance of big data workflows and ensure data quality. Collaborate with business and technical stakeholders to gather and translate data requirements. Implement best practices for data integration, processing, and governance. Required Qualifications Bachelor’s degree in Computer Science, Engineering, or a related field. 2–10 years of experience in data engineering or a similar role. Strong experience with SQL, Spark SQL, and PySpark. Hands-on experience with Databricks for big data processing. Proven experience with BI tools such as Power BI and/or Tableau. Strong understanding of data warehousing and ETL/ELT concepts. Good problem-solving skills and the ability to work in cross-functional teams. Nice To Have Experience with cloud data platforms (Azure, AWS, or GCP). Familiarity with CI/CD pipelines and version control tools (e.g., Git). Understanding of data governance, security, and compliance standards. Exposure to data lake architectures and real-time streaming data pipelines. Show more Show less
