Data Engineer US

1 month ago

Novi, United States Sails Software Inc Full time

Would you be interested in exploring career opportunities with us?

Please find the job description below.

Job Title: Data Engineer (On-site)

Client: Equifax

Position: C2C or 1099

Location: Atlanta GA Onsite

St. Louis MO Onsite

Working Hours: 8 Hours/Per Day

What you'll do

  • Conduct data wrangling and data analyses in a big data environment; Create business insights and KPI reporting using Equifax's credit data and alternative data assets.
  • Working with D&A, IT, and Google Cloud Migration team, automate data reporting and scoring processes on Google Cloud
  • Collaborate with D&A Data Scientists and analytical consultants executing compelling analytical projects that demonstrate the value of Equifax data assets and products.
  • Articulate and educate various internal stakeholders on Equifax data and analytical solutions.
  • Use Airflow to perform a variety of data aggregation, data quality, and integrity checks.
  • Use Airflow for automating multiple jobs with dependencies, parallelizing jobs, monitoring run status, failures and troubleshooting, and more.
What experience you need
  • Master's or higher degree in Computer Science, Information Technology, Data Science, MIS, or other quantitative disciplines
  • 4+ Years' experience with data engineering in Financial Services or credit reporting companies
  • 2 years experience with structured and unstructured data and accessing data using languages such as SQL
  • 2 years of GCP and Python scripting experience
  • Expert knowledge of SQL and Python, or equivalent data analytics tools used for large-scale data analysis and modeling
  • Hands-on experience in data wrangling, data cleaning, data automation, and subsequent data monitoring and analysis
  • Hands-on experience in using Apache Airflow and Dataproc to programmatically author, schedule, and monitor workflows
What could set you apart
  • Knowledge of various sources of data such as credit bureau, consumer credit, demographics, and income data is preferred.

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