
Senior Data Engineering Specialist
2 days ago
We are seeking a highly skilled Data Engineer to join our team. This role requires hands-on experience in designing, developing, and managing data pipelines and transformation frameworks that enable analytics, reporting, and business intelligence capabilities across the enterprise.
The ideal candidate will work closely with data architects, platform engineers, and DevOps teams to build scalable, resilient, and efficient data engineering solutions using modern Azure tools and best practices.
Key Responsibilities:
- Design and Build Scalable ETL/ELT Pipelines
- Develop and optimize PySpark/Spark SQL jobs for large-scale batch and streaming data transformations.
- Ingest data from various sources including Apache Kafka, REST APIs, and RDBMS, ensuring real-time or near-real-time availability.
- Implement data modeling strategies (star schema, snowflake schema) for analytics consumption layers in Synapse or ADLS.
- Collaborate with DevOps Teams
- Collaborate with DevOps teams to automate deployment using CI/CD pipelines (Azure DevOps, GitHub Actions, etc.).
- Monitor, troubleshoot, and optimize data workflows for performance, cost-efficiency, and reliability.
- Support Data Quality and Observability
- Support data quality checks, logging, alerting, and observability mechanisms for production workloads.
- Participate in sprint ceremonies and contribute to task estimation and delivery planning.
Required Skills and Qualifications:
- 5+ years of experience in data engineering roles.
- Strong in SQL, Python, and Spark for data manipulation and transformation.
- Exposure to CI/CD practices (Azure DevOps, Git workflows, build/release pipelines).
Preferred Certifications:
- Microsoft Certified: Azure Data Engineer Associate
- Databricks Certified Associate Developer for Apache Spark
- Azure Fundamentals (AZ-900)
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