Data Engineer
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Job Location:
Monthly Salary:
Posted on:
19-10-2025
Vacancies:
1 Vacancy
Job Summary
Key Responsibilities
- Design develop and maintain scalable data pipelines using PySpark and Azure Data Factory.
- Work closely with business stakeholders analysts and data scientists to understand data requirements and deliver reliable solutions.
- Optimize ETL workflows for performance scalability and reliability.
- Implement best practices for data ingestion transformation and integration across multiple sources.
- Ensure data quality governance and security across the data lifecycle.
- Troubleshoot and resolve issues related to data pipelines storage and performance.
Required Skills & Qualifications
- 5 years of total experience with 3 years relevant in PySpark Azure Data Factory and Python.
- Strong experience in building large-scale data pipelines and ETL workflows.
- Hands-on expertise in PySpark for data processing and transformation.
- Proficiency in Azure Data Factory (ADF) for orchestrating and automating workflows.
- Solid understanding of Python for scripting data handling and automation.
- Strong SQL skills and ability to work with relational and non-relational databases.
- Good knowledge of data warehousing concepts and performance optimization.
- Exposure to Azure ecosystem (Data Lake Databricks Synapse Analytics etc.) preferred.
- Excellent problem-solving analytical and communication skills.
Nice to Have (Optional)
- Experience with CI/CD pipelines for data solutions.
- Knowledge of data governance security and compliance frameworks.
- Familiarity with real-time data streaming technologies (Kafka Event Hubs etc.).
Additional Details
- Cloud Preference: Azure only (AWS experience not required).
- Budget/CTC Range: 18 LPA.
- Contract/Full-Time: Full-Time
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
