Data Engineer/Senior Data Engineer


Pristina, XK
  • Job Type: Full-Time
  • Function: Data Science
  • Industry: Technology
  • Post Date: 05/12/2022
  • Website:
  • Company Address: 56 Roland St, Boston, Massachusetts 02129, US

About Tive

Tive in-transit visibility solutions help shipping and logistics professionals manage their shipments and eliminate preventable delays and damage.

Job Description

At Tive we imagine a world fully transparent, where everything and everyone is connected. We want to pioneer beyond what the world thought possible so what others hold near and dear arrives on time and in full.
We believe and live four core company values:
1. Create transparency first, everything else second: We believe the strongest trust belongs to those who are transparent, open and deliver on their word.
2. Make it simple: We expect to do the work and deliver technical solutions to complex problems, simply.
3. At Tive, we’ve got your back: We hold fierce loyalty to our people.
4. Relentless iteration to find a better way: Our energy to learn new things and create solutions every day is unmatched anywhere in the world.
Tive exists to solve the real time visibility challenges related to one of the world’s largest and most complex networks: global logistics and supply chain. Our team is focused on giving our customers the most access to accurate, live, and meaningful information about their shipments. Whether by road or rail, ocean or air, Tive is the most innovative and accurate way for companies to track their cargo.
As a Data Engineer at Tive, you will help lead the company into the next phase by being a critical part of the infrastructure being developed ensuring that we can continue to deliver the best possible information and service to our customers as we scale.

Our ideal candidate will have:

      • A strong understanding of data modeling, relational databases, statistics, and relevant data profiling algorithms,
      • Strong Python and SQL skills, 
      • Experience with big data streaming platforms such as AWS Kinesis or Apache Kafka, 
      • Experience building AWS Lambdas and APIs in Python, 
      • Strong analytical skills with the ability to analyze, profile and validate data to identify potential data quality issues, 
      • Hands on data validation experience on AWS or similar cloud technologies and SQL databases, 
      • Experience working with large streaming time series datasets, 
      • Excellent interpersonal and written/verbal communication skills 
In addition, they may have:
    • Experience in a multi-dimensional data environment, 
    • Previous work supporting data science pipelines and teams, 
    • Familiarity with one or more data quality monitoring and/or data profiling software packages such as Great Expectations or PyDeequ, or equivalent managed tool, 
    • Familiarity with Agile development methodologies such as Scrum, 
    • Experience with AWS hosting environments and DevOps, 
    • Working knowledge of C#, 
    • Experience using Docker and/or Kubernetes to build containerized applications, and
    • MS or work experience equivalent in computer science/mathematics/physics or related technical field.

What you’ll be doing:

    • You will write ETL processes, develop database systems, and help develop tools for real-time and offline analytic processing.
    • You will collaborate with the data science team to transform data and integrate algorithms and models into automated processes using tools like AWS Lambda and API Gateway or similar technologies.
    • You will implement an automated data quality monitoring system and an automated ETL testing at the enterprise level.
    • You will work to build strong relationships with and support co-workers, including remote peers in other time zones.
    • You will contribute to a fast paced, world class team whilst helping grow the company that aims to make this the best place you’ve ever worked.
We celebrate diversity and consider it key to our success as a team and a company. We are proud to be an equal opportunity employer, and we are committed to creating an inclusive environment of mutual respect for all employees.

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