AI Data Engineer

Overview

At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.

Specialized expertise in Databricks and comprehensive experience implementing bronze, silver, and gold data pipelines. You will leverage your skills in Snowflake, Google BigQuery (GBQ), Python, and Google Cloud Platform (GCP) to build, optimize, and maintain robust data solutions supporting AI and analytics workloads. In this critical role, you'll collaborate closely with data scientists, AI specialists, cloud engineers, and business stakeholders to deliver scalable, secure, and performant data platforms.

Duties & Responsibilities

• Data Pipeline Development & Optimization
  • Design, build, and maintain data pipelines using Databricks, implementing bronze, silver, and gold data layers.
  • Continuously optimize data ingestion, transformation, and loading processes to improve performance, reliability, and scalability.
  • Ensure high data quality standards through robust validation, auditing, and governance frameworks.
• Cloud Data Platforms Expertise
  • Manage and optimize data solutions on Snowflake and Google BigQuery, ensuring efficient querying and resource utilization.
  • Develop strategies to migrate, integrate, and synchronize data between various cloud data warehouses.
  • Implement best practices for cloud data management, ensuring cost-effective and secure operations.
• Python & Automation
  • Leverage Python to automate data processes, streamline workflows, and develop efficient data transformations.
  • Build and manage automation scripts and workflows for data extraction, cleaning, and loading into various platforms.
  • Collaborate with AI teams to develop data integration points and data access layers supporting machine learning workloads.
• GCP Infrastructure
  • Utilize GCP services (Cloud Storage, BigQuery, Dataflow, Pub/Sub, Composer) to architect and deploy scalable data systems.
  • Integrate GCP infrastructure seamlessly with Databricks and other analytics environments.
  • Ensure robust cloud infrastructure monitoring, logging, and alerting mechanisms to proactively identify and mitigate data pipeline issues.
• Data Governance & Security
  • Establish comprehensive data governance practices, ensuring compliance with regulatory standards (e.g., GDPR, HIPAA).
  • Implement robust data security practices including encryption, role-based access control, and auditing mechanisms.
  • Collaborate closely with security and compliance teams to maintain secure data operations.
• Collaboration & Communication
  • Partner with data scientists, engineers, analysts, and business stakeholders to understand and fulfill data infrastructure requirements.
  • Clearly communicate complex data engineering concepts and solutions to technical and non-technical audiences.
  • Actively participate in agile methodologies, contributing to sprint planning, retrospectives, and continuous improvement initiatives.

Hiring Requirements

• Education: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related fields (or equivalent experience).
• Experience: 3-5+ years of experience as a data engineer, with specific expertise in Databricks and structured data pipeline architectures (bronze, silver, gold).
• Technical Skills: Proficient in Databricks platform management, data pipeline construction, and optimization. Strong expertise in Snowflake and GBQ, including data modeling, query optimization, and performance tuning. Advanced proficiency in Python, particularly for data manipulation, ETL processes, and automation. Extensive experience with GCP data services including Cloud Storage, BigQuery, Pub/Sub, and Dataflow.
• AI & Analytics Integration: Understanding of AI and analytics data requirements, including data preparation and feature engineering. Experience building data solutions supporting machine learning model training, validation, and deployment.
• Portfolio: Evidence of successful data engineering projects involving Databricks and cloud data warehouses. Examples demonstrating complex pipeline management and data architecture contributions.

Equal Opportunity Employer

Globe's hiring process promotes equal opportunity to applicants. Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as posting vacancies, selecting, and interviewing applicants. Globe's Diversity, Equity and Inclusion Policy Commitment can be accessed here.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Information Technology

Industries

• Telecommunications

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