Data Engineer-Databricks & SQL

As a Data Engineer at our company, you will play a crucial role in our data team's growth and success. With 6 to 10 years of experience in data engineering, proficiency in SQL, Databricks, Spark SQL, PySpark, and BI tools like Power BI or Tableau, you are well-equipped to take on the responsibilities that come with this position. Your primary responsibilities will include designing and developing scalable data pipelines using PySpark and Databricks, crafting efficient SQL and Spark SQL queries for data transformation and analysis, and collaborating closely with BI teams to facilitate reporting through Power BI or Tableau. Additionally, you will be tasked with optimizing the performance of big data workflows, ensuring data quality, and implementing best practices for data integration, processing, and governance. To excel in this role, you should hold a Bachelor's degree in Computer Science, Engineering, or a related field, along with 6 to 10 years of experience in data engineering or a similar capacity. Your strong command over SQL, Spark SQL, PySpark, and Databricks, as well as your familiarity with BI tools such as Power BI and/or Tableau, will be essential in delivering high-quality results. Moreover, your expertise in data warehousing, ETL/ELT concepts, and problem-solving skills will be invaluable as you collaborate with various stakeholders. While not mandatory, experience with cloud data platforms (Azure, AWS, or GCP), knowledge of CI/CD pipelines and version control tools like Git, and an understanding of data governance, security, and compliance standards would be advantageous. Exposure to data lake architectures and real-time streaming data pipelines will further enhance your capabilities in this role. This is a full-time position based in Noida, Uttar Pradesh, requiring in-person work. In return, we offer health insurance benefits and a day shift schedule. If you meet the qualifications and possess the requisite experience, we encourage you to apply and become a valuable part of our dynamic data team.,