Senior Data Engineer

Date:  Apr 19, 2024
Location: 

Bengaluru, KA, IN, 560092 Mumbai, MH, IN, 400033

Company:  Cimpress Technology

Cimpress India is looking for Senior Data Engineers across Bengaluru and Mumbai locations.


 

Job Description:

We are searching for an energetic, self-motivated Data Engineer with strong technical, analytical, organizational, and collaboration skills to work in our Fulfillment Technology Software services group.

You are comfortable in a rapidly evolving environment, taking on new and diverse responsibilities based on the needs of the business. You are self-directed with a strong bias for action who takes accountability for your performance and are comfortable working independently or on cross-functional, global teams.


 

What will you do:

  • Build robust data pipelines for real-time and analytical data in Snowflake using AWS or other related tools.
  • Use DBT to implement ELT pipelines, with optimal scheduling, data validation, quality checks and proper documentation.
  • Perform data curation duties on new or enhanced datasets - this includes modeling raw data into datasets, perform quality assurance/quality control, documentation, and cataloging activities.
  • Support the team in suggesting and implementing new features or improvements to data infrastructure. Support and suggest improvements to the scheduling/Snowflake infrastructure at hand.
  • Help build data products (Dashboards, simulations, predictive analyses etc.).
  • Recognize, track and analyze trends and patterns for the fulfilment and shipping portion of our Mass Customization Platform as well as our diverse set of logistics operations users. As a result, you are both detail- and delivery-oriented. You can phone in on value while at the same time, have a willingness to explore tangents to figure out why something doesnt look quite right.
  • Explore ML use-cases in shape of forecasts, optimizations and predictions, aimed at enhancing customer satisfaction and improving overall supply chain planning.
  • Be immersed in diverse teams (e.g., Product Owners, Logistics Managers, Software Developers, etc.) where you will collaborate on building data products and continually bring forward ideas and insights to drive value for our customers.


 

Requirements: You

  • Have very strong English written, verbal, communication, and presentation skills;
  • Can manage and execute ad-hoc and exploratory analytic requests, database queries and generate reports ;
  • Can collaborate virtually with team members and stakeholders with multiple functions and levels;
  • Disseminate information in a structured way and include it in a dashboard software;
  • Possess business and situational awareness of how information drives an organization;
  • Are intensely curious, learn quickly, and apply new tools and techniques;
  • Can explore and recommend presentation technologies to contribute to building and evolving dashboards and control towers for logistics managers;


 

Qualifications

  • Bachelors degree in Business, Mathematics, Statistics, Computer Science, Engineering, Economics or any related field;
  • 5-7 years of relevant data engineering, data infrastructure, DataOps / MLOps, DevOps
  • Familiarity or expertise using and maintaining modern data platform technologies and services with Snowflake, Airflow, Fivetran, DBT, Looker, etc.
  • Expose to AWS infrastructure is a plus.
  • Understanding of DevOps and CI/CD Pipelines and pathological inclination towards automation;
  • Experience in ML focused data engineering aspects like data curation, feature extraction, training data is a plus;
  • A solid grasp of SQL fundamentals and strong coding ability in Python (preferred) or other languages C#, Golang, etc.
  • Full lifecycle ownership up through production and experience with observability and monitoring tools like New Relic;
  • Knowledge of Looker or any other analytic, reporting, data visualization tools (Looker, Tableau, Qlik, SSRS, etc.), is a plus;


Job Segment: Logistics, Supply Chain, Quality Assurance, QA, Computer Science, Operations, Quality, Technology