About the Role
Our client, a leading financial services firm, is seeking a Senior Data Engineer with a strong background in big data technologies and full-stack development. This is a high-impact role where you'll contribute to the design, development, and optimization of enterprise-grade data solutions that power key analytics and business decisions.
Key Responsibilities
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Design, develop, and maintain scalable data pipelines using Hadoop, PySpark, and Databricks SQL.
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Lead the development of complex, full-stack features and data-driven applications that support critical business needs.
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Collaborate across technical, data, and business teams to translate business requirements into scalable technical solutions.
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Utilize modern open-source tools and techniques, including machine learning, predictive analytics, and advanced statistics, to support deep-dive analysis and modeling.
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Ensure data quality, governance, and security standards are upheld throughout the development lifecycle.
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Continuously optimize performance and cost-efficiency of data processing workflows.
Required Skills & Experience
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5+ years of full-stack engineering experience in a fast-paced, agile environment.
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Proven track record in leading the design and implementation of large, complex technical features in full-stack and data-driven applications.
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Expertise in Python, PySpark, and working within Hadoop ecosystems.
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Strong experience writing performant Databricks SQL queries and working in a cloud-based data platform.
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Ability to bridge gaps between business goals and technical solutions, with a strong grasp of business use cases and data requirements.
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Experience applying advanced data science techniques, including machine learning and predictive modeling, using modern open-source tools.