GCP Data Lead
United States
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Job Description
GCP Data Lead
Phoenix, Arizona

Job Summary

Big Data / GCP Data Engineer

Must-Have and Nice-to-Have Skills

Must-Have Skills

  • Education: Bachelor’s or Master’s degree in Computer Science, Computer Engineering, another technical discipline, or equivalent work experience.
  • Experience: 5+ years of hands-on software development experience with Big Data and analytics solutions.
  • GCP and Big Data: Hands-on experience with Google Cloud Platform technologies, including BigQuery, Dataproc, Pub/Sub, and Airflow, plus Hadoop, Hive, and Spark.
  • Programming and scripting: Strong Python and shell-scripting skills.
  • Data engineering: Strong experience designing, developing, and optimizing scalable data pipelines for large-scale data processing, transformation, and analysis.
  • SQL and data modelling: Proficiency in SQL and relational database systems, including designing and optimizing data models for performance and scalability.
  • Event processing: Experience building event-driven processing pipelines using Kafka or Google Cloud Pub/Sub.
  • Distributed systems: Knowledge of distributed, multi-tiered systems and algorithms.
  • Software engineering: Strong object-oriented programming skills and knowledge of design patterns.
  • CI/CD and source control: Experience with CI/CD pipelines, automated testing frameworks, and source-code management tools such as Jenkins and Git.
  • Problem solving: Ability to analyze complex data-engineering problems, propose effective solutions, and implement them successfully.
  • Enterprise frameworks: Ability and willingness to learn, adopt, and build solutions using established enterprise Big Data frameworks.
  • Collaboration: Effective communication with product and cross-functional teams.
  • Delivery methodology: Understanding of SDLC methodologies and familiarity with Agile and Scrum ceremonies.
  • Continuous improvement: Proactive approach to identifying improvement opportunities and willingness to learn and apply new technologies.

Nice-to-Have Skills

  • Workflow and messaging tools: Additional design and development experience with Airflow, Pub/Sub, and Kafka.
  • DevOps tooling: Experience with Git, GitHub, Jenkins, XLR, and configuration-management practices.
  • Regulatory technology: Experience building innovative engineering solutions for financial-crimes compliance.
  • Engineering excellence: Experience improving resilience, predictability, delivery efficiency, and automation within engineering teams.
  • Product partnership: Experience partnering with product teams to envision and deliver technology-led transformation.
  • Certification: Google Cloud Professional Data Engineer certification.

 

Key Responsibilities

Big Data / GCP Data Engineer

Must-Have and Nice-to-Have Skills

Must-Have Skills

  • Education: Bachelor’s or Master’s degree in Computer Science, Computer Engineering, another technical discipline, or equivalent work experience.
  • Experience: 5+ years of hands-on software development experience with Big Data and analytics solutions.
  • GCP and Big Data: Hands-on experience with Google Cloud Platform technologies, including BigQuery, Dataproc, Pub/Sub, and Airflow, plus Hadoop, Hive, and Spark.
  • Programming and scripting: Strong Python and shell-scripting skills.
  • Data engineering: Strong experience designing, developing, and optimizing scalable data pipelines for large-scale data processing, transformation, and analysis.
  • SQL and data modelling: Proficiency in SQL and relational database systems, including designing and optimizing data models for performance and scalability.
  • Event processing: Experience building event-driven processing pipelines using Kafka or Google Cloud Pub/Sub.
  • Distributed systems: Knowledge of distributed, multi-tiered systems and algorithms.
  • Software engineering: Strong object-oriented programming skills and knowledge of design patterns.
  • CI/CD and source control: Experience with CI/CD pipelines, automated testing frameworks, and source-code management tools such as Jenkins and Git.
  • Problem solving: Ability to analyze complex data-engineering problems, propose effective solutions, and implement them successfully.
  • Enterprise frameworks: Ability and willingness to learn, adopt, and build solutions using established enterprise Big Data frameworks.
  • Collaboration: Effective communication with product and cross-functional teams.
  • Delivery methodology: Understanding of SDLC methodologies and familiarity with Agile and Scrum ceremonies.
  • Continuous improvement: Proactive approach to identifying improvement opportunities and willingness to learn and apply new technologies.

Nice-to-Have Skills

  • Workflow and messaging tools: Additional design and development experience with Airflow, Pub/Sub, and Kafka.
  • DevOps tooling: Experience with Git, GitHub, Jenkins, XLR, and configuration-management practices.
  • Regulatory technology: Experience building innovative engineering solutions for financial-crimes compliance.
  • Engineering excellence: Experience improving resilience, predictability, delivery efficiency, and automation within engineering teams.
  • Product partnership: Experience partnering with product teams to envision and deliver technology-led transformation.
  • Certification: Google Cloud Professional Data Engineer certification.

 

Skill Requirements

Big Data / GCP Data Engineer

Must-Have and Nice-to-Have Skills

Must-Have Skills

  • Education: Bachelor’s or Master’s degree in Computer Science, Computer Engineering, another technical discipline, or equivalent work experience.
  • Experience: 5+ years of hands-on software development experience with Big Data and analytics solutions.
  • GCP and Big Data: Hands-on experience with Google Cloud Platform technologies, including BigQuery, Dataproc, Pub/Sub, and Airflow, plus Hadoop, Hive, and Spark.
  • Programming and scripting: Strong Python and shell-scripting skills.
  • Data engineering: Strong experience designing, developing, and optimizing scalable data pipelines for large-scale data processing, transformation, and analysis.
  • SQL and data modelling: Proficiency in SQL and relational database systems, including designing and optimizing data models for performance and scalability.
  • Event processing: Experience building event-driven processing pipelines using Kafka or Google Cloud Pub/Sub.
  • Distributed systems: Knowledge of distributed, multi-tiered systems and algorithms.
  • Software engineering: Strong object-oriented programming skills and knowledge of design patterns.
  • CI/CD and source control: Experience with CI/CD pipelines, automated testing frameworks, and source-code management tools such as Jenkins and Git.
  • Problem solving: Ability to analyze complex data-engineering problems, propose effective solutions, and implement them successfully.
  • Enterprise frameworks: Ability and willingness to learn, adopt, and build solutions using established enterprise Big Data frameworks.
  • Collaboration: Effective communication with product and cross-functional teams.
  • Delivery methodology: Understanding of SDLC methodologies and familiarity with Agile and Scrum ceremonies.
  • Continuous improvement: Proactive approach to identifying improvement opportunities and willingness to learn and apply new technologies.

Nice-to-Have Skills

  • Workflow and messaging tools: Additional design and development experience with Airflow, Pub/Sub, and Kafka.
  • DevOps tooling: Experience with Git, GitHub, Jenkins, XLR, and configuration-management practices.
  • Regulatory technology: Experience building innovative engineering solutions for financial-crimes compliance.
  • Engineering excellence: Experience improving resilience, predictability, delivery efficiency, and automation within engineering teams.
  • Product partnership: Experience partnering with product teams to envision and deliver technology-led transformation.
  • Certification: Google Cloud Professional Data Engineer certification.

 

Other Requirements
Maximum Salary (US): 
Minimum Salary (US): 
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Information at a Glance

Why HCLTech?

At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion. 

 

Compensation and Benefits

A candidate’s pay within the range will depend on their skills, experience, education, and other factors permitted by law. This role may also be eligible for performance-based bonuses subject to company policies. In addition, this role is eligible for the following benefits subject to company policies: medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance; employee assistance program; 401(k) retirement plan; 10 days of paid time off per year (some positions are eligible for need-based leave with no designated number of leave days per year); and 10 paid holidays per year.