
Status Neo
1 day ago
About the Role
We are seeking a skilled and results-driven Data Engineer who can combine technical expertise with strong business understanding. This role demands hands-on experience with modern Azure data stack tools, agile delivery practices, and the ability to solve real-world data challenges at scale. You will play a key role in building and optimizing scalable data pipelines, data lakes, and data transformation workflows that power business insights and AI-driven solutions.
Key Responsibilities :
- Design, develop, and maintain scalable data pipelines using Azure Data Factory and Azure Databricks.
- Manage and optimize storage solutions using Azure Data Lake Storage (Gen2) and Delta Lake.
- Write efficient and reusable code in SQL for data extraction, transformation, and loading (ETL/ELT).
- Integrate and automate workflows across data ingestion, cleansing, validation, and transformation processes.
- Work closely with data analysts, architects, and business teams to gather data requirements and deliver solutions.
- Ensure data governance, quality, and security standards are met across data platforms.
- Participate in code reviews, performance tuning, and continuous improvement of data engineering practices.
- Stay updated with emerging trends in cloud data engineering, analytics, and AI/ML integrations.
Required Skills & Experience :
- 3 - 6 years of hands-on experience as a Data Engineer or in a similar role.
Proven expertise in the Azure data ecosystem, including:
- Azure Data Factory (ADF)
- Azure Databricks
- Azure Data Lake Storage (ADLS Gen2)
- Delta Lake
- Strong command of SQL for querying, transformation, and performance optimization.
- Basic scripting skills in Python for data manipulation and automation tasks.
- Understanding of distributed data processing concepts and performance tuning.
Good to Have :
- Experience with Apache Spark for big data processing.
- Familiarity with Microsoft Fabric (MS Fabric) for integrated data workflows.
- Understanding of Data Warehouse concepts, including dimensional modeling and star/snowflake schemas.
- Exposure to Generative AI (GenAI) or AI-based data applications.
- Experience in data visualization and dashboard tools is a plus.
(ref:hirist.tech)
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