Data Engineer

Tiger Analytics; United States; Remote; USD 80,000 - 130,000; Full time

Job summary

Join a forward-thinking company as a Data Engineer, where you will design and build scalable data pipelines and ETL workflows. Collaborate with Data Scientists and ML Engineers to implement data requirements, utilizing cutting-edge tools like Databricks and Snowflake. This role offers the chance to work on impactful projects with global clients in a collaborative environment. With a focus on continuous learning and career development, this position is perfect for those looking to make a significant impact in the world of data engineering. Flexible working arrangements are available, making it an ideal opportunity for professionals seeking work-life balance.

Benefits

Collaborative work environment

Opportunities for impactful projects

Competitive salary and benefits

Continuous learning opportunities

Flexible working arrangements

Qualifications

• 6+ years of experience in data engineering or related roles.
• Strong expertise in cloud platforms and data processing frameworks.

Responsibilities

• Design and maintain efficient data pipelines and ETL workflows.
• Develop high-performance data processing systems using distributed computing.

Skills

Python

SQL

Apache Spark

Hadoop

Data Governance

ETL Workflows

Cloud Platforms (AWS, Azure, GCP)

Data Modeling

Problem-Solving

Communication Skills

Education

Bachelor’s Degree in Computer Science

Master’s Degree in Data Engineering

Tools

Databricks

Snowflake

AWS Glue

Azure Data Factory

GCP BigQuery

Job description

About Us

At Tiger Analytics, we are a global leader in advanced analytics, AI, and data engineering solutions. Collaborating with some of the world’s most recognized brands, we solve complex business challenges with cutting-edge technology. We are looking for experienced Data Engineers in Mexico to join our team and contribute to transformative data solutions.

Key Responsibilities

• Design, build, and maintain efficient, scalable data pipelines and ETL workflows.
• Partner with Data Scientists, ML Engineers, and business stakeholders to understand and implement data requirements.
• Develop high-performance data processing systems using distributed computing frameworks like Apache Spark or Hadoop.
• Architect and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Work extensively with tools such as Databricks and Snowflake for data processing and analytics.
• Optimize and troubleshoot cloud-based data workflows for performance, scalability, and cost-efficiency.
• Implement robust data governance practices to ensure quality, consistency, and compliance.
• Work with structured and unstructured data across relational and NoSQL databases.
• Mentor junior team members and contribute to best practices in data engineering.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• 6+ years of experience in data engineering or related roles.
• Strong expertise in cloud platforms (AWS, Azure, or GCP), including services like AWS Glue, Azure Data Factory, and GCP BigQuery.
• Hands-on experience with Databricks and Snowflake for large-scale data processing and analytics.
• Proficiency in Python, SQL, and data processing frameworks such as Apache Spark or Hadoop.
• Deep understanding of ETL workflows and best practices for large datasets.
• Familiarity with data modeling, data warehousing, and database architecture.
• Experience ensuring data security and governance compliance.
• Excellent problem-solving and communication skills.
• Fluency in English; Spanish is a plus.

• A collaborative and innovative work environment.
• Opportunities to work on impactful projects with global clients.
• Competitive salary and benefits tailored to mid to senior professionals.
• Continuous learning and career development opportunities.
• Flexible working arrangements based in Mexico.