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Minimum of 5 years of experience as a Data Engineer or in a similar role.
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Strong hands-on experience with Databricks and Apache Spark.
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Advanced SQL and Python skills.
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Experience working in cloud environments (Azure preferred).
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Solid understanding of data modeling, ETL/ELT processes, and data architecture concepts.
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Ability to work independently while collaborating with distributed teams.
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Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark.
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Define data architectures that support batch and streaming processing.
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Integrate data from multiple sources, including databases, APIs, and cloud storage.
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Optimize data solutions for performance, reliability, and cost efficiency.
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Collaborate closely with data science, analytics, and business teams.
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Provide technical leadership and guidance on data engineering best practices.
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Translate complex Databricks architectures and data solutions into clear, business-friendly explanations for technical and non-technical audiences.
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Document data architectures, pipelines, and technical decisions.
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Support production systems and troubleshoot data-related issues as needed.
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Experience designing enterprise-scale data platforms.
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Experience building, supporting, and scaling production-grade data pipelines in enterprise environments.
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Exposure to analytics, BI, or data science workloads.
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Familiarity with CI/CD practices for data engineering.
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Strong communication skills with both technical and non-technical stakeholders. Any certifications for Databricks or Apache are a plus.
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Competitive salary
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Flexible work environment
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Opportunities for growth and certifications
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Inclusive and collaborative team culture
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Access to cutting-edge tools and technologies
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