Senior Data Engineer (AWS) - Marketing

Truelogic is a leading provider of nearshore staff augmentation services, located in New York. Our team of 500 tech talents is driving digital disruption from Latin America to the top projects in U.S. companies. Truelogic has been helping companies of all sizes to achieve their digital transformation goals.

Would you like to make innovation happen? Have you ever dreamed of building Products that impact millions of users? Nice! Then we have a seat for you on our team!

What are you going to do?

You will have the opportunity to work in a forward-thinking and growth-oriented environment, at an evolved dating app and a home for relationships.

Occupy a unique position in the market, ee are seeking a Data Engineer to design, develop, and maintain data pipelines that will power our AI models and user analytics. The role involves handling large-scale data ingestion, transformation, and storage using AWS services. You will ensure that our data infrastructure is scalable, reliable, and optimized for AI/ML models.

• Design and build data pipelines for ingestion, transformation, and storage using AWS services (Glue, Kinesis, Redshift).
• Ensure data quality and reliability across data processing and storage layers.
• Collaborate with the AI/ML team to provide clean, well-structured data for model training and inference.
• Optimize data pipelines for scalability and performance.
• Implement data governance, security, and compliance measures to protect user data.
• Monitor data flows and troubleshoot issues in real-time to ensure system reliability.

What will help you succeed

• 5+ years of experience as a Data Engineer, with expertise in building data pipelines using AWS.
• Proficiency in data processing frameworks and tools (e.g., Apache Spark, AWS Glue, Kinesis).
• Strong understanding of ETL processes and data architecture design.
• Experience with SQL and NoSQL databases, including DynamoDB and Redshift.
• Strong understanding of data privacy and security best practices.
• Experience with big data technologies and real-time data processing.