Data Architect (Remote)

Innowhyte Inc; Irvine (CA); Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Flexible work from home

Direct interaction with CXO team

Career growth opportunities

Job summary

A technology company is seeking a skilled Data Engineering Lead/Architect to design and maintain scalable data pipelines. The ideal candidate will have over 5 years of experience in data engineering, with strong skills in Python, cloud platforms like AWS or GCP, and data pipeline frameworks. This role offers the flexibility to work from home and involves collaboration with cross-functional teams to drive impactful data projects. Competitive compensation and opportunities for career growth are included.

Qualifications

• Minimum 5+ years of hands-on experience in data engineering or related roles.
• Proven expertise in handling large-scale data systems.
• Familiarity with Generative AI (GenAI) and AI/ML technologies.

Responsibilities

• Design, develop, and maintain robust data pipelines for analytics.
• Collaborate with teams to implement data-driven solutions.
• Optimize data storage systems for reliability and performance.

Skills

Python programming

Data pipelines

Cloud platforms

Data processing libraries (e.g., Pandas, PySpark)

Version control

Education

Bachelor's or Master’s degree in Computer Science, Engineering

Tools

Apache Airflow

Kafka

Spark

Job description

We are seeking a highly skilled and experienced Data Engineering Lead/Architect to join our dynamic team. The ideal candidate will have a proven track record of designing, building, and maintaining scalable data pipelines, with strong expertise in Python programming, cloud technologies, and large-scale data systems. If you have a passion for working with data and enabling AI/ML capabilities in products, we want to hear from you.

Key Responsibilities

• Design, develop, and maintain robust and scalable data pipelines to support analytics and machine learning applications.
• Collaborate with cross-functional teams, including data scientists and software engineers, to implement data-driven solutions.
• Optimize and manage data storage systems and ensure high availability, reliability, and performance.
• Design, develop, and maintain robust and scalable ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) data pipelines to support analytics and machine learning applications.
• Ensure data pipelines are optimized for efficiency, reliability, and scalability, handling both structured and unstructured data seamlessly.
• Handle large-scale datasets, ensuring data integrity and consistency across platforms.
• Provide technical expertise and mentorship to junior engineers and stakeholders.
• Implement best practices in data engineering, including version control, testing, and deployment.
• Stay updated with emerging technologies and tools in data engineering, AI/ML, and cloud ecosystems.

Requirements

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Minimum 5+ years of hands-on experience in data engineering or related roles.
• Proficiency in Python programming and its data-processing libraries (e.g., Pandas, PySpark).
• Proven expertise in handling large-scale data systems such as distributed databases, data warehouses, and data lakes.
• Strong experience with cloud platforms (AWS, Azure, or GCP) and associated tools for data storage, processing, and orchestration.
• Practical knowledge of data pipeline frameworks like Apache Airflow, Kafka, or Spark.
• Hands-on technical expertise in designing and implementing end-to-end data solutions.
• Familiarity with Generative AI (GenAI) and AI/ML technologies.

What We Offer

• Enjoy the flexibility to work from the comfort of your home, with no commute hassles.
• Work directly with the CXO team, gaining valuable insights and contributing to strategic decisions.
• Take the opportunity to initiate, own, and drive impactful data engineering projects across the organization.
• Become a key member of the engineering leadership team, driving innovation and excellence within the data domain.
• Work with state-of-the-art technologies in AI, ML, and data engineering.
• Competitive compensation and ample opportunities for career growth.