At evolv Consulting, we are seeking to hire an experienced Senior Data Engineer to join our team. If you’re a passionate self-starter, evolv is a great place to get ahead.
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Leads the design of scalable big data platform/solutions used to ingest and process accurately scaled traffic data.
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Bring together large, complex and sparse data sets to meet functional and non-functional business requirements via design and implementation of effective data tools alongside data scientist team members to help them in building, optimizing and tuning our product.
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Integrate new data management technologies and software engineering tools into existing structures.
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Build end-to-end solutions that enable business stakeholders, BI engineers, and analysts to self-serve their business intelligence needs.
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Develop and automate large scale, high-performance, scalable platform (batch and/or streaming) to drive faster analytics.
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Design, construct, install, test and maintain highly scalable data pipelines with state-of-the-art monitoring and logging practices.
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Experience in building and maintaining custom frameworks to support engineering/analytics needs.
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Knowledge of continuous integration, testing methodologies, TDD and agile development methodologies.
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Partner with analytic consumers and data scientists to build and improve new/existing constructs and solve data engineering problems at a large scale.
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Good knowledge of Data formats (Parquet, ORC etc.) and consensus management systems.
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Exposure to structured or unstructured storage and distributed caching.
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Deploy inclusive data quality checks to ensure high quality of data.
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Experienced Engineer or Contributor or Committer to open-source technologies is plus.
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Evangelize high quality software engineering practices towards building data infrastructure and pipelines at scale.
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Structured thinking with ability to easily break down ambiguous problems and propose impactful solutions.
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Attention to detail and effective verbal/written communication skills.
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Other duties as assigned.
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Use a variety of languages, tools and frameworks to marry data and systems together.
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Recommend ways to improve data reliability, efficiency and quality.
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Other duties as assigned.
