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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable, optimized enterprise-level data pipelines for real-time and batch processing using Scala, Apache Spark, and Azure Databricks.
Collaborate with cross-functional teams and business stakeholders to translate requirements into data solutions and operationalize machine learning models.
Ensure data quality, governance, and operational excellence while mentoring junior engineers and contributing to code reviews and technical documentation.
Minimum Requirements
7+ years of experience in data engineering or related fields with 5+ years building data pipelines for structured and unstructured data.
2+ years of experience with big data technologies such as PySpark, Hadoop, Kafka, EventHub, and Stream Analytics.
3+ years of experience in SQL Server, T-SQL, stored procedures, performance tuning, and data warehousing concepts including relational and dimensional data modeling.
3+ years experience with Azure Data Factory, Azure Data Lake, Azure SQL DB, and Azure Synapse Analytics; Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
Ideal Candidate Profile
Experienced in designing and optimizing large-scale data architectures, comfortable with end-to-end pipeline development and operationalizing ML models.
Skilled in collaborating across teams including data scientists and business stakeholders to deliver data-driven solutions aligned to business use cases.
Familiar with Agile/Scrum methodologies, DevOps practices, CI/CD pipelines, version control (Git), and holds or is competitive for Azure Data Engineer Certification.