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Job Description
Structured overview of role & requirementsAbout This Role
Build, automate, and industrialize Big Data pipelines and platforms within a shared Big Data environment.
Lead stakeholder discussions and manage the full data engineering lifecycle including requirement gathering, system design, data ingestion, testing, deployment, and operational support.
Provide innovative solutions to complex data problems and ensure project delivery status reporting and ongoing maintenance post-implementation.
Minimum Requirements
5-8 years of experience in building Data Pipelines and working with Big Data ecosystems like Hadoop and Spark.
Strong coding skills in Python, Java, or Scala.
Experience with Azure Data Engineering stack including Data Factory, Event Hubs, Data Lake Storage, Databricks, and Synapse Analytics.
Understanding of data integration patterns (Medallion, Kappa), data modeling, and Cloud architecture with preferred Azure certification.
Ideal Candidate Profile
Experienced in managing both batch and streaming large volume structured and unstructured data pipelines.
Familiar with Agile methodologies and tools such as JIRA, with operational expertise in DevOps toolchains like Kubernetes, Jenkins, and Gitlab.
Capable of collaborating effectively with cross-functional teams to deliver scalable data engineering solutions aligned with business needs.