Data Engineer II

Job Description Summary

We are seeking a Data Engineer to help design and build modern data platforms that power analytics, artificial intelligence, automation, business applications, and digital transformation initiatives.

You will play a critical role in creating scalable, governed, and reliable data foundations that enable organizations to make better decisions, develop intelligent solutions, and accelerate innovation. Working alongside business stakeholders, architects, software engineers, analysts, and AI practitioners, you will transform fragmented data into trusted, reusable, and high-value data assets. This role aligns with initiatives involving governed data foundations, AI-ready knowledge assets, analytics enablement, and enterprise platform integration.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and data platforms.

• Build and optimize data lakes, warehouses, and modern cloud-based data architectures.

• Integrate data from enterprise systems, applications, APIs, documents, and operational platforms.

• Develop reusable data products that support reporting, analytics, machine learning, automation, and AI solutions.

• Implement data quality, governance, lineage, metadata, and monitoring frameworks.

• Support the development of intelligent applications through well-structured and AI-ready datasets.

• Collaborate with technical and business teams to translate requirements into scalable solutions.

• Champion best practices in data engineering, platform reliability, automation, and security.

• Contribute to the evolution of enterprise data and AI platforms.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, Data Science, or a related field.

• 4+ years of experience in Data Engineering, Analytics Engineering, Data Platform Engineering, or similar roles.

• Strong proficiency in SQL and Python.

• Experience building ETL/ELT pipelines and modern data architectures.

• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.

• Strong understanding of data modeling, data warehousing, and data management principles.

• Experience integrating data from multiple systems and APIs.

• Knowledge of data governance, security, privacy, and quality management practices.

• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with cloud-native services for data storage, orchestration, and analytics.

• Experience building enterprise data lakes, lakehouses, or knowledge repositories.

• Familiarity with business intelligence and analytics platforms such as Power BI or Tableau.

• Experience supporting AI, machine learning, generative AI, or intelligent automation initiatives.

• Knowledge of DevOps, CI/CD, Infrastructure-as-Code, and platform engineering practices.

• Experience working in large-scale transformation, analytics, technology, or innovation programs.

Technical Skills

• SQL

• Python

• Data Modeling

• Data Warehousing

• Data Lakes & Lakehouse Architectures

• Cloud Computing (AWS/Azure/GCP)

• ETL / ELT Development

• API Integration

• Data Governance

• Data Quality Management

• DevOps & CI/CD

• Business Intelligence

• Machine Learning Data Pipelines

• Generative AI & Knowledge Platforms

What We're Looking For

A builder who can think strategically about data, architect scalable solutions, and create the foundation that enables analytics, AI, automation, and digital products to succeed. The ideal candidate is comfortable operating across engineering, architecture, business requirements, and emerging technologies while maintaining a strong focus on quality, governance, and business value.