Data Engineer with ML Engineering Experience IRC260071

Description

GlobalLogic is hiring a Data Engineer with ML Engineering Experience for one of largest mobile communications customer. #LI-SC3

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. A Master’s degree or relevant certifications (e.g., Google Professional Data Engineer) is a plus
• 5+ years of experience in data engineering, with at least 2-3 years of experience in machine learning engineering or deploying ML models in production.
• Proven experience in building and maintaining scalable data pipelines, data warehouses, and infrastructure to support ML workflows.

Job responsibilities

Requirements:

Technical Skills

• Proficiency in big data frameworks and tools such as Apache Spark, Hadoop, Kafka, and Airflow.
• Advanced skills in data modeling, ETL processes, and data pipeline automation, with a focus on performance and scalability.
• Experience with cloud platforms (AWS, GCP, Azure) and their data services, such as AWS Glue, Google BigQuery, or Azure Data Lake.
• Strong programming skills in Python, SQL, and experience with data query optimization.
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn) and libraries for building and testing machine learning models.
• Knowledge of containerization and orchestration tools (Docker, Kubernetes) for deploying and managing ML models in production.

Machine Learning Engineering Skills

• Experience in feature engineering, data preprocessing, and building data pipelines to support ML training and inference.
• Knowledge of MLOps best practices for continuous integration, deployment, and monitoring of ML models in production.
• Familiarity with model lifecycle management tools such as MLflow, TFX, or Databricks to streamline ML workflows.
• Strong understanding of data versioning, reproducibility, and monitoring of ML models to ensure model integrity over time.
• Ability to work with structured and unstructured data, with hands-on experience in NLP, computer vision, or time-series data for machine learning applications.

Data Engineering Skills

• Proficiency in data storage and warehousing solutions (e.g., Snowflake, Redshift, BigQuery) for scalable data architecture.
• Understanding of data governance, quality, and security best practices, including data lineage and compliance with regulations.
• Experience with data lake architecture and data partitioning strategies to support large-scale data analysis.
• Ability to optimize data infrastructure for low-latency access and high throughput, especially for real-time ML applications.

Communication and Collaboration Skills

• Strong communication skills with the ability to work closely with data scientists, ML engineers, and product teams to align data infrastructure with business requirements.
• Collaborative mindset, with experience working in cross-functional teams to deliver end-to-end data and ML solutions.
• Ability to document data workflows, pipelines, and ML infrastructure, ensuring transparency and ease of knowledge sharing.
• Proven ability to understand and respond to the needs of diverse stakeholders, from technical teams to business leaders.

Additional Qualifications

• Familiarity with A/B testing, experimentation frameworks, and data-driven evaluation of ML models.
• Knowledge of data privacy and security regulations (e.g., GDPR, CCPA) for responsible data management and ML practices.
• Experience in specific industries like Telcomunications is a plus.
• Passion for staying up-to-date on the latest in data engineering, ML tools, and techniques, with a proactive approach to continuous learning.

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.