Sr. Data Engineer

3 days ago

India Amicon Hub Services Full time

At QSpark Group Inc, we rely on insightful data to power our systems and solutions. As a Data Engineer you will be working with the core team to build data pipelines, data analytics and helping our clients derive value from their data.

We all know that data is hot and that companies need to use the data to come to insights. But do they know who is using their data? And which data?

As a data engineer, you will support our clients to take control of their data and getting value out of it by creating the best data pipelines, data warehouses or ETL processes for our customers. This means that you will work closely with information management teams.


Responsibilities

·     Analyze and organize raw data

·     Build data systems and pipelines

·     Evaluate business needs and objectives

·     Interpret trends and patterns

·     Conduct complex data analysis and report on results

·     Prepare data for prescriptive and predictive modeling

·     Build algorithms and prototypes

·     Combine raw information from different sources

·     Explore ways to enhance data quality and reliability

·     Identify opportunities for data acquisition

·     Develop analytical tools and programs

·     Collaborate with data scientists and architects on several projects.


Required skills and qualifications

  • 8+ years experience in enterprise data pipeline building/ETL workflow
  • Previous experience as a data engineer or in a similar role
  • Technical expertise with data models, data mining, and segmentation techniques
  • Knowledge of programming languages (e.g. Java and Python)
  • Hands-on experience with SQL database design
  • Great numerical and analytical skills
  • Degree in Computer Science, IT, or similar field; a Master’s is a plus
  • Data engineering certification is a plus.
  • Manage data sets and work with ETL and Data warehouse solutions.


Preferred skills and qualifications

  • Bachelor’s degree (or equivalent) in Computer Science or equivalent
  • Two or more years of working experience on large scale data projects


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