Data Transformation Specialist
2 days ago
We are a cutting-edge technology company dedicated to harnessing the power of data transformation. Our team is comprised of innovators who continuously strive for excellence in scalable data pipeline design.
Estimated Salary: ₹1,200,000 - ₹1,500,000 per annumJob DescriptionAs a Data Transformation Specialist, you will play a pivotal role in designing and implementing efficient data pipelines to support big data transformations and analytics. You will work closely with cross-functional teams to deploy and manage data systems on cloud platforms such as Azure, AWS, or Google Cloud.
You will be responsible for utilizing orchestration tools like Azure Data Factory and other cloud-native services for data pipeline automation. Additionally, you will write high-performance scripts using SQL, PySpark, Scala, and Python (Databricks experience preferred).
Key responsibilities include working with big data technologies like Hadoop, Spark, Hive, Snowflake, and Kafka to process and manage large datasets. You will also design and implement dimensional data models for data warehouses and data marts.
Furthermore, you will use monitoring and logging tools (Prometheus, Grafana, Splunk) to ensure system performance and troubleshoot issues. Collaboration with cross-functional teams using project management tools like JIRA and Azure DevOps is essential.
Developing reports and dashboards using Power BI or similar visualization tools is crucial in delivering actionable insights. Qualifications include a Bachelor's degree in Computer Science, Engineering, or a related field, along with 5-7 years of experience in data engineering.
Strong proficiency with cloud platforms (Azure preferred), including experience with services like Azure Data Factory, is required. Expertise in scripting languages such as SQL, Python, PySpark, and/or Scala; experience with Databricks is a plus.
Experience with big data technologies including Hadoop, Spark, Hive, Snowflake, and Kafka is necessary. A strong understanding of dimensional modeling and experience designing data warehouses and data marts is also required.
Familiarity with monitoring/logging tools such as Prometheus, Grafana, or Splunk is necessary. Proficiency in Power BI or similar data visualization tools to create insightful reports and dashboards is essential.
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