
Senior Data Architect
5 days ago
Job Title: Data Engineering Specialist
We are seeking an experienced data engineer to play a critical role in designing, developing, and managing data pipelines and transformation frameworks that enable analytics, reporting, and business intelligence capabilities across the enterprise.
You 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.
Data Pipeline Development:
- Design and build scalable ETL/ELT pipelines using Azure Data Factory (ADF), Azure Databricks (Spark), and Azure Synapse Analytics.
- 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.
Key Responsibilities:
- Data Modeling: Implement data modeling strategies (star schema, snowflake schema) for analytics consumption layers in Synapse or ADLS.
- Coding Standards and Version Control: Follow coding standards, participate in peer reviews, and maintain version-controlled code in Git repositories.
- Data Quality and Observability: Support data quality checks, logging, alerting, and observability mechanisms for production workloads.
Must-Have Skills:
- 5+ years of experience in data engineering roles.
- Hands-on experience with Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, Apache Kafka, SQL, Python, and Spark.
- Strong understanding of data lake architecture and modern data warehousing principles.
Nice-to-Have Skills:
- Experience with Delta Lake, Event Hub, or Azure Stream Analytics.
- Familiarity with infrastructure-as-code tools like Terraform or ARM templates.
- Exposure to Data Governance, Data Quality frameworks, or metadata management.
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