Senior Staff Data Engineer

September 17

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Financial Services • Responsible Lending • Pre-Paid Debit Cards • Serving the Underbanked • Data Analytics

1001 - 5000

Description

• Set the strategic vision and lead the implementation of a cutting-edge data infrastructure roadmap, encompassing all facets as highlighted above. • Provide exceptional technical leadership, mentoring, and guidance to a team of data engineers, fostering a culture of continuous learning and innovation. • Collaborate closely with data scientists to translate intricate model requirements into optimized data pipelines, ensuring impeccable data quality, processing, and integration. • Spearhead the establishment of best practices for model versioning, experiment tracking, and model evaluation to ensure transparency and reproducibility. • Engineer automated CI/CD pipelines that facilitate seamless deployment, monitoring, and continuous optimization for code and configurations in data engineering. • Define and refine performance benchmarks, and optimize data infrastructure to achieve peak correctness, availability, cost efficiency, scalability, and robustness. • Highly motivated self-starter who loves ownership and responsibility while working in a collaborative and interdependent team environment. • Work with multiple teams of data engineers to design, develop, and test major software and data systems components using an agile, scrum methodology. • Drive strong data engineering practices around product development execution, operational excellence in observability, quality, reliability, and developer efficiency. • Remain at the forefront of industry trends and emerging technologies, expertly integrating the latest advancements into our data ecosystem.

Requirements

• Requires 12+ years of related experience in data engineering, with a Bachelor's degree in Computer Science; or a Master's degree with an equivalent combination of education and experience. • Extensive experience orchestrating the development of end-to-end data engineering infrastructure for intricate and large-scale applications. • Proven record of transformative leadership, guiding technical teams to achieve remarkable outcomes and innovation. • Profound mastery of data engineering architecture and frameworks across batch and stream processing of data, such as Hadoop ecosystem, Medallion architecture, Databricks or equivalent data warehouse / data lake platforms, coupled with Python / PySpark programming. • Thorough comprehension of software engineering principles, version control (Git), and collaborative development workflows. • Adeptness with cloud platforms (AWS / Azure / GCP) and utilization of cloud-native services for crafting robust data engineering infrastructure. • Track record of successfully integrating DevOps practices, continuous integration, and continuous deployment (CI/CD) pipelines. • Superior problem-solving acumen and ability to navigate intricate technical challenges with dexterity. • Exceptional communication aptitude, capable of fostering effective collaboration across diverse teams and stakeholders.