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Job ID : 35090

Location : Ohio City, OH

Company Name : Atechstar

Job Type : Full-Time, Part-Time, Contract, Training

Industry : Information Technology

Salary : $54000 - $65000  per year

No. of Positions : I have ongoing need to fill this role


Required Skills : Database tools, Data transformation tools, Data ingestion tools..

Benefits : Medical Insurance, Dental Insurance, Vision Insurance, 401K, Life Insurance


Job Description :

Responsibilities:

  • Partner with COO, Head of Technology, and Engineering Leads for digital assets to evaluate data providers and implement strategic roadmap for the research platform.
  • Analyze real-time and historical digital asset data sources and work to integrate into firm platforms similar to existing asset classes
  • Gather and process raw data at scale (including writing systems and scripts, calling APIs, write SQL queries, etc.).
  • Build solutions to process unstructured data into a form suitable for analysis and ingest into the platform. This includes a strong emphasis on data quality and resiliency.
  • Work with other members of the team to ensure data is ingested, stored, and managed properly to support our analytical needs.
  • Helping define automation and management of cloud infrastructure and services using native tools, open source tools, and third party products.
  • Implement platform telemetry and reliability systems for performance tuning and troubleshooting, and to trigger automated actions based on events or thresholds.

Qualifications:

  • 4+ years of experience building scalable and reliable data pipelines based on Big Data processing technologies like Hadoop, Cassandra, MapReduce, Spark, etc.
  • 4+ years of combined hands-on experience in Java and Python, with examples of reusable and efficient code to automate analyses and data processes.
  • 2+ years of experience deploying and managing cloud environments for data pipelines and intelligence services for digital assets.
  • Experience processing large amounts of structured and unstructured data from disparate sources with strong emphasis on quality controls and resiliency.
  • Strong knowledge of and experience with statistics; potentially other advanced math as well.
  • Broad understanding of financial services instruments helpful.

Key Skills:

  • Database tools. 
  • Data transformation tools. 
  • Data ingestion tools.
  • Data mining tools. 
  • Data warehousing and ETL tools. 
  • Real-time processing frameworks. 
  • Data buffering tools. 
  • Machine Learning skills.

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