Data Engineer (Hybrid/Guadalajara or Tijuana)

Insulet; Región Centro; Presencial; MXN 934,000 - 1,309,000; Jornada completa

Descripción de la vacante

A leading medical technology firm in Mexico is seeking a Data Engineer to manage the data lake infrastructure. This role involves working with various teams to ensure quality data processing and developing tools for analytics. The ideal candidate will have experience in data technologies and a strong educational background in STEM fields. The position offers exciting career growth within a fast-paced environment.

Formación

• Experience in data quality assurance and control for large datasets.
• Experience managing robust ETL/ELT pipelines.
• Experience in medical device or manufacturing industries is desirable.

Responsabilidades

• Design, implementation and maintenance of data lake and architecture.
• Work with cross-functional teams to identify data sources.
• Develop data preprocessing tools as needed.

Conocimientos

SQL and relational databases

Cloud data management (Azure SQL, Google BigQuery)

Python

ETL and workflow tools

Non-relational databases (MongoDB)

Educación

Bachelor's degree in Mathematics, Computer Science, Electrical and Computer Engineering

Master's degree in relevant fields or BS with 2-3 years experience

Herramientas

Azure Data Factory

AWS Glue

Descripción del empleo

Position Overview

Insulet Corporation, maker of the OmniPod, is the leader in tubeless insulin pump. The Data Engineer role is responsible for data lake infrastructure, development of automated data uploads and scripting for data cleansing and analytics. Reporting to the Senior Director, Global Technology and Cloud Ops, you will develop tools and processes to transform data for use with Insulet’s Analytics team and senior technical leaders. We are a fast growing company that provides an energetic work environment and tremendous career growth opportunities.

Responsibilities

• Design, implementation and maintenance of Insulet’s data lake, warehouse and overall architecture
• Work with IT, analytics and cross functional teams to identify data sources, determine data collection and design aggregation mechanisms
• Perform data quality checks and data clean up
• Interface with business stakeholders in cross-functional teams, including manufacturing, quality assurance, and post-market surveillance in order to understand various applications and their data sets
• Develop data preprocessing tools as needed
• Maintenance and understanding of the various business intelligence tools used to visualize and report team analytics results to the company

Education and Experience

• Bachelors degree in Mathematics, Computer Science, Electrical and Computer Engineering, or a closely related STEM field is required
• Master’s degree in Mathematics, Computer Science, Electrical and Computer Engineering, or a closely related STEM field; or a BS with 2-3 year’s experience working with data technologies, is preferred
• Experience in data quality assurance, control and lineage for large datasets in relational/non-relational databases
• Experience managing robust ETL/ELT pipelines for big real-world datasets that could include messy data, unpredictable schema changes and/or incorrect data types
• Experience with both batch data processing and streaming data
• Experience in implementing and maintaining Business Intelligence tools linked to an external data warehouse or relational/non-relational databases is required
• Experience in medical device, healthcare, or manufacturing industries is desirable
• HIPAA experience a plus

Skills/Competencies

• Demonstrated knowledge in SQL and relational databases is required
• Knowledge in non-relational databases (MongoDB) is a plus
• Demonstrated knowledge of managing large data sets in the cloud (Azure SQL, Google BigQuery, etc) is required
• Knowledge of ETL and workflow tools (Azure Data Factory, AWS Glue, etc) is a plus
• Demonstrated knowledge of building, maintaining and scaling cloud architectures (Azure, AWS, etc), specifically cloud data tools that leverage Spark, is required
• Demonstrated coding abilities in Python, Java, C or scripting languages
• Demonstrated familiarity with different data types as inputs (e.g. CSV, XML, JSON, etc)
• Demonstrated knowledge of database and dataset validation best practices
• Demonstrated knowledge of software engineering principles and practices
• Ability to communicate effectively and document objectives and procedures