Sr. Big Data Engineer (relocation to US, onsite)

We are seeking an experienced and highly skilled Senior Big Data Engineer to architect, build, and optimize large-scale data processing systems. This role will involve leading the design and implementation of advanced data pipelines, ensuring the scalability and reliability of big data infrastructure, for many of our clients.

We are particularly interested in talented individuals in Mexico who are willing to relocate to the United States for this opportunity.

We will also assist with the TN visa process to facilitate your move to the U.S. Once you land a project in the U.S., you will be eligible for a comprehensive benefits package. This is a full-time consulting opportunity where you will be working with several clients around the United States.

Key Responsibilities:

• Architect and implement high-performance big data platforms using technologies like Hadoop, Spark, and Kafka.
• Develop scalable, secure, and efficient ETL/ELT pipelines for structured and unstructured data.
• Optimize the performance of data processing jobs and storage across batch and real-time systems.
• Integrate data from multiple sources including APIs, relational databases, NoSQL stores, and event streams.
• Collaborate closely with data scientists, analysts, and DevOps to deliver production-grade data solutions.
• Define and enforce data engineering best practices, coding standards, and performance benchmarks.
• Ensure compliance with data governance, privacy, and security regulations. • Lead code reviews, technical discussions, and mentoring sessions.

Sr. Big Data Engineer Required Skills and Experience:

• 4+ years of experience in big data engineering or related roles.
• Bachelor’s degree in computer science, Information Technology, or a related field.
• Advanced English (written/spoken) as you will be going on US-based projects.
• Expertise in backend programming using Python and Scala (Java or C++ is a plus).
• Strong SQL skills, including aggregate/window functions, stored procedures, views, complex joins, DDL, and DML.
• Hands-on experience with Big Data technologies: Apache Spark, Hadoop, Kafka, Hive, Flink, and NoSQL databases (MongoDB, Cassandra, HBase).
• Experience with cloud-based data platforms (AWS, AZURE, GCP)
• Proficiency with Snowflake and Databricks for cloud-based data processing and analytics.
• Experience with ETL/ELT pipelines, real-time streaming solutions, and distributed computing principles.
• Strong understanding of data modeling, data lakes, data warehousing, data security, and compliance best practices.
• Familiarity with containerization and orchestration tools (Docker, Kubernetes, Airflow).
• Knowledge of CI/CD pipelines for data engineering.
• Strong problem-solving, analytical, and troubleshooting skills.
• Ability to design, build, and optimize data solutions in a cloud environment.
• Experience with Agile methodologies and project management.
• Knowledge of Python, SQL (Scala is a plus).

Preferred Qualifications:

• Experience with machine learning pipelines and MLOps tools.
• Knowledge of real-time data processing frameworks (e.g., Flink, Storm).
• Contributions to open-source big data projects or certifications (e.g., Cloudera, Databricks, AWS Big Data Specialty).
• Experienced in working with US-based companies within your career.