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Job ID : 35173

Location : Manchester, MI

Company Name : VISART

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

Industry : Information Technology

Salary : $106200 - $107700  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 :


  • Work with product managers and data analysts to build data products that power our business.
  • Build and maintain data analytics reports, ETL pipelines, data lakes, and streaming solutions.
  • Analyze new data sources and work with stakeholders to understand the impact of integrating new data into existing pipelines and models
  • Develop & maintain critical data pipelines, using tools such as Apache Airflow, to ensure highly accurate and reliable business reporting
  • Perform ad-hoc analysis and provide insights to stakeholders within the organization such as Marketing, Growth & Sales teams to drive prioritization.
  • Create data visualizations and analytic reports using various tools such as Tableau, Databox, etc
  • Optimize database queries to improve and maintain performance on very large data sets.
  • Work closely with the business and data science team for the deliverables.
  • Masters or bachelor's degree in CS/ML/AI or relevant computational/engineering discipline.
  • Experience building stream-processing systems, using solutions such as Kinesis, Kafka, Storm or Spark-Streaming.
  • Expertise with coding with Pyspark, Pandas, Scipy, and visualizations with Tableau & Databox. Scheduling/orchestrating pipelines using Databricks and Airflow.
  • Expertise with data querying (SQL, Redshift, Spark) and analyzing billions of rows of data points.
  • Familiarity with SQL, especially within cloud-based data warehouses like Snowflake, Google BigQuery, and Amazon Redshift
  • Strong understanding of relational DB such as MySQL/PostgreSQL, document-based storage systems such as MongoDB or CouchDB, key-value stores Column-oriented stores graph-oriented stores; their distinct advantages, disadvantages, and trade-offs.
  • Experience building machine learning, statistical and analytical models, and tuning parameters.
  • Experience designing experiments and extracting insights.

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. 

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