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Data Engineer with ML Engineering Experience IRC248524Job: IRC248524
Location: Argentina - Buenos Aires
Designation: Senior Data Designer
Experience: 5-10 years
Function: Data Design
Skills: Airflow, Apache Spark, Cloud(Azure/AWS/GCP), ETL, Hadoop, Kafka, Python
Work Model: Remote
We are looking for a Senior Data Engineer with ML Engineering Experience to join our team!
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: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 Telecommunications 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 OfferExciting Projects: Come take your place at the forefront of digital transformation! With clients across all industries and sectors, we offer an opportunity to work on market-defining products using the latest technologies.
Collaborative Environment: Expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global centers or client facilities!
Work-Life Balance: GlobalLogic prioritizes work-life balance, which is why we offer flexible work schedules. We offer you the best quality of work life so that you exceed the expectations of our clients while achieving your professional and personal ambitions.
Professional Development: Our dedicated Learning & Development team regularly organizes English classes, professional certifications, and technical and soft skill trainings. We also offer the chance to travel internationally.
Excellent Benefits: We provide our employees with competitive salaries, family medical insurance, extended paternity leave, annual performance bonuses, and referral bonuses.
About GlobalLogicGlobalLogic is a leader in digital engineering. We help brands across the globe design and build innovative products, platforms, and digital experiences for the modern world. By integrating experience design, complex engineering, and data expertise—we help our clients imagine what's possible and accelerate their transition into tomorrow's digital businesses. Headquartered in Silicon Valley, GlobalLogic operates design studios and engineering centers around the world, extending our deep expertise to customers in the automotive, communications, financial services, healthcare and life sciences, manufacturing, media and entertainment, semiconductor, and technology industries. GlobalLogic is a Hitachi Group Company operating under Hitachi, Ltd. (TSE: 6501) which contributes to a sustainable society with a higher quality of life by driving innovation through data and technology as the Social Innovation Business.
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