Remote Senior Data Engineer

Summary

Join our team at Truelogic, a leading provider of nearshore staff augmentation services, to work on innovative projects that impact millions of users. As a Data Engineer, you will analyze and categorize inbound data, establish data pipelines, and ensure seamless connectivity to move data into Snowflake or a similar Datalake.

Requirements

• 3+ years of experience as a Data Engineer or in a similar role
• Proven experience with ETL/ELT processes and data pipeline development
• Hands-on experience with data integration tools like Airbyte, Fivetran, or similar
• Proficiency in SQL and experience with relational databases
• Experience working with cloud data warehouses, particularly Snowflake
• Familiarity with workflow orchestration tools such as Apache Airflow
• Programming skills in Python or another relevant language
• Knowledge of data modeling, data warehousing concepts, and data architecture

Responsibilities

• Analyze inbound data sources to understand structure, quality, and formats
• Categorize data based on relevance, sensitivity, and usage requirements
• Collaborate with stakeholders to define data schemas and metadata
• Establish connectivity to various data sources, including APIs, databases, and file systems
• Develop and configure data ingestion pipelines using tools like Airbyte or Fivetran to move data into Snowflake
• Ensure data is loaded, then transformed, cleaned, and stored appropriately for downstream use
• Implement data governance policies, including data ownership and access controls
• Ensure compliance with data protection regulations (e.g., GDPR, CCPA)
• Implement encryption, authentication, and authorization mechanisms to secure data
• Work closely with cross-functional teams, including data scientists, developers, and project managers
• Create and maintain documentation, including data dictionaries and pipeline designs
• Communicate progress and issues to relevant stakeholders
• Monitor and optimize data pipeline performance
• Troubleshoot and resolve data-related issues
• Plan for scalability to handle increased data volumes and additional data sources