Data Engineer
3 weeks ago
Job Title : Data Engineer
Location : Gurugram, Delhi
Experience : 3-5 Years
Budget : 24 LPA
Work Mode : Work From Office (WFO)
Interview Mode : Virtual
Must-Have Skills : PySpark, Databricks, ML Flow, Azure DevOps, SQL
Job Description :
We are seeking a skilled Data Engineer to design, build, and maintain data pipelines, data architectures, and ETL processes using advanced tools and technologies. The ideal candidate will have hands-on experience with PySpark, Databricks, and Azure DevOps, and will be proficient in building scalable solutions for data processing and analytics.
As a Data Engineer, you will collaborate with global teams, including data science and business intelligence, to ensure efficient data handling and gain insights that drive business decisions
Key Responsibilities :
- Data Pipeline Development: Design and build data pipelines using Spark-SQL and PySpark within Azure Databricks to handle large datasets efficiently.
- ETL Pipeline Design: Develop ETL pipelines using Azure Data Factory (ADF) for robust data transformation and integration.
- Lakehouse Architecture: Build and maintain a Lakehouse architecture in ADLS/Databricks, ensuring scalable and efficient data storage and processing.
- Data Preparation: Perform data preparation tasks including cleaning, normalization, deduplication, and type conversion for optimized data usability.
- Collaboration with DevOps: Work closely with the DevOps team to deploy data solutions in production environments using Azure DevOps.
- Error Handling: Monitor data processes, identify errors, and execute corrective actions, ensuring data integrity. This includes troubleshooting and resolving root causes of data errors.
- Global Team Collaboration: Participate as a member of the global analytics team, collaborating on projects, sharing insights, and adopting best practices from data science and business intelligence colleagues.
- Project Leadership: Lead and participate in projects, applying change management tools to manage upgrades, changes, and data migrations. This includes training, documentation, and communication efforts.
Qualifications :
- 3 to 5 years of experience in data engineering, with a strong focus on PySpark, Databricks, and Azure DevOps.
- Expertise in designing and building ETL pipelines using ADF.
- Strong knowledge of Lakehouse architecture and ADLS/Databricks.
- Solid experience with SQL for database queries and data management.
- Proven ability to collaborate with global teams and lead data projects.
- Strong problem-solving skills and attention to detail in managing data processes and errors.
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