Job
Description
Here Its Detailed Job description Below, We are seeking a Principal Data Engineer with deep expertise in Java and Apache Spark to lead the design and implementation of scalable data solutions across our enterprise. You will be responsible for setting technical direction, mentoring team members, and delivering high-performance data pipelines that drive business insights and innovation. As a technical leader, youll collaborate closely with data scientists, software engineers, product managers, and DevOps teams to ensure data is accurate, accessible, and actionable. Key Responsibilities: Design and implement scalable, distributed data processing systems using Apache Spark (batch and streaming) and Java-based frameworks. Architect end-to-end data pipelines for ingestion, transformation, and storage of structured and unstructured data. Lead technical discussions, code reviews, and mentor a team of data engineers. Optimize performance and cost-efficiency of data workflows on cloud platforms (e.g., AWS, GCP, or Azure). Ensure best practices in data modeling, code quality, and data governance. Work cross-functionally with analytics, machine learning, and software engineering teams to meet business objectives. Stay current with industry trends and evaluate emerging technologies for continuous improvement. Preferred Qualifications: Experience working with cloud-native data services (e.g., AWS Glue, EMR, GCP Dataflow, or Azure Synapse). Proficiency in other languages such as Python or Scala. Familiarity with data security, compliance, and privacy best practices (GDPR, HIPAA, etc.). Contributions to open-source projects or participation in technical communities is a plus.
