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Senior Python Data Engineer

Tecnología
HCLTech
Hace 1 mes
Tiempo completoPresencial

Descripción del puesto

Introduction to the Organization

HCLTech is a global leader in technology and IT services, recognized for delivering innovative solutions that empower organizations to transform digitally. With a presence in over 50 countries and a diverse workforce exceeding 220,000 employees, HCLTech is committed to fostering a culture of innovation, collaboration, and excellence. The company has achieved industry acclaim for its client-centric approach, cutting-edge technologies, and a strong focus on sustainability and social responsibility.

Overview of the Role

As a Senior Python Data Engineer, you will play a pivotal role in architecting and delivering robust enterprise-grade data solutions that drive critical business insights and efficiencies. You will lead the development of scalable data pipelines and frameworks, ensuring data quality, reliability, and performance for mission-critical applications. Your expertise will directly impact the digital transformation journeys of our clients, supporting HCLTech’s mission to deliver operational excellence and innovation at scale.

Detailed Responsibilities

  • Design, develop, and implement enterprise-grade data solutions using Python, with advanced utilization of Pandas and NumPy for large-scale data processing.
  • Build, optimize, and maintain scalable ETL/ELT pipelines for data ingestion, preprocessing, cleansing, transformation, validation, and enrichment.
  • Develop reusable frameworks and components to support efficient and maintainable data engineering operations.
  • Optimize data pipelines for enhanced performance, reliability, and operational efficiency in production environments.
  • Apply software engineering best practices, including clean code principles, modular architecture, automated testing, and thorough code reviews.
  • Transform analytical prototypes into production-ready, industrialized solutions.
  • Design, implement, and maintain CI/CD pipelines to automate build, test, deployment, and release processes.
  • Manage Python deployment artifacts, packages, and libraries for production use.
  • Implement and maintain monitoring, logging, alerting, and observability capabilities for data services.
  • Provide production support, troubleshooting, and proactive resolution for deployed applications.
  • Collaborate effectively with multidisciplinary teams and stakeholders to translate business requirements into technical solutions.
  • Ensure solutions adhere to the highest standards of scalability, robustness, security, and operational excellence.
  • Champion and contribute to Agile development methodologies.
Skill Requirements
  • Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
  • Extensive hands-on experience in Python programming, with advanced expertise in data engineering libraries such as Pandas and NumPy.
  • Proven track record in building and optimizing ETL/ELT pipelines for complex, large-scale datasets.
  • Strong foundation in data engineering processes: ingestion, preprocessing, cleansing, transformation, validation, and enrichment.
  • Deep understanding of software engineering best practices, including DevOps principles and the software delivery lifecycle.
  • Experience in designing and maintaining CI/CD pipelines for automated deployments.
  • Proficiency in creating and managing Python packages and deployment artifacts in production environments.
  • Familiarity with cloud platforms, particularly Azure or similar cloud environments.
  • Experience with monitoring, logging, and alerting tools for production data services.
  • Demonstrated ability to collaborate with multidisciplinary teams and manage stakeholder expectations effectively.
  • Excellent problem-solving skills and results-oriented mindset.
Other Requirements (Optional)
  • Professional certifications in cloud platforms (e.g., Azure Certified Data Engineer, AWS Data Analytics) are a plus.
  • Experience with additional data engineering tools and frameworks (Spark, Airflow, Kafka, etc.) is advantageous.
  • Exposure to machine learning model deployment and MLOps practices is a bonus.
  • Strong verbal and written communication skills for technical documentation and stakeholder interactions.
Career Development Opportunities At HCLTech, we are committed to nurturing talent and fostering long-term career growth. You will have access to:
  • Continuous learning through global training programs, certifications, and workshops on the latest technologies and methodologies.
  • Clear career progression paths and leadership development initiatives.
  • Opportunities to work on cutting-edge projects for Fortune 500 clients, expanding your expertise and industry exposure.
  • Internal mobility across geographies and business units, supporting your professional aspirations.
  • A supportive and inclusive culture that values innovation, diversity, and work-life balance.
Keywords
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