Data Engineer

Job Summary

The Data Engineer will design, build, and maintain scalable ETL pipelines to support massive data ingestion, transformation, and integration from disparate sources. Key functions include optimizing complex MySQL schemas, developing robust data models within modern data warehousing environments, writing advanced Python automation scripts, and authoring precise technical blueprints to ensure data accuracy, consistency, and absolute security across all pipelines.

Qualification

Candidates must meet the following baseline communication, structural, and environmental standards:

• Required Degree: Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related quantitative field (or equivalent professional hands-on expertise).
• Remote Operational Readiness: Highly self-motivated, disciplined, and capable of managing and prioritizing critical data engineering tasks independently in a dynamic, work-from-home framework.
• Communication Metrics: Excellent written and verbal English communication skills, with a heavy emphasis on drafting clear, precise system documentation and collaborating effectively across remote lines.
• Engineering Precision: A deeply detail-oriented mindset with an uncompromising commitment to delivering reliable, secure, and highly optimized data solutions.

Note: Formal AI/ML training is explicitly not required; micro1 prioritizes your applied database engineering and software development domain knowledge.

Experience

Candidates must demonstrate direct, hands-on technical competence in database tuning, ingestion pipeline construction, and automated scripting:

Core Data Engineering Mastery

• Expert-Level MySQL: Verifiable mastery of MySQL database engines, including writing highly complex queries, advanced database schema design, indexing, query optimization, and rigorous performance tuning.
• Production Python Scripting: Strong programming proficiency using Python specifically for advanced data manipulation, file parsing, and data workflow automation.
• ETL Architecture Construction: Hands-on experience architecting, deploying, and maintaining automated Extract, Transform, Load (ETL) pipelines within active production environments.
• Data Warehousing Foundations: Demonstrated deep expertise with core data warehousing concepts, including dimensional modeling (Star/Snowflake schemas), data abstraction layers, and modern data lifecycle best practices.

Advanced Infrastructure & Methodologies (Preferred)

• Cloud-Based Warehouses: Direct experience leveraging cloud data warehouse platforms such as Snowflake, AWS Redshift, or Google BigQuery.
• Advanced Data Architecture: Practical experience handling complex logical and physical data modeling, data governance frameworks, or advanced database migrations.
• Agile Ecosystems: Familiarity with agile development methodologies, version control systems (Git), and continuous code deployment workflows.

Key Responsibilities

Pipeline Architecture & Ingestion Management

• Build Scalable ETL/ELT: Design, develop, and maintain high-throughput ETL pipelines to support data ingestion, cleaning, transformation, and integration from multiple source networks.
• Govern Data Models: Formulate and continuously optimize advanced logical and physical data models to support stable data warehousing frameworks.
• Automate Data Workflows: Leverage advanced SQL queries and robust Python scripts to remove manual friction, automate data processes, and optimize continuous infrastructure routines.

Infrastructure Tuning & Performance Engineering

• Optimize MySQL Performance: Audit internal database instances to eliminate latency blocks, optimize complex join commands, and tune query performance under heavy analytical loads.
• Troubleshoot Core Assets: Monitor, diagnose, and enhance data infrastructure endpoints to guarantee optimal performance, minimal downtime, and infinite scalability.
• Enforce Platform Security: Implement strict validation checks across all processing streams to guarantee data accuracy, structural consistency, and absolute data safety.

Cross-Functional Collaboration & Documentation

• Partner Globally: Collaborate closely with distributed, cross-functional engineering cells to deeply understand evolving technical data requirements and deliver reliable infrastructure solutions.
• Author Precise Blueprints: Document complex technical processes, system designs, ingestion workflows, and data flows with extreme clarity and precision.
• Deliver AI Training Inputs: Translate complex data schemas into structurally sound training blocks, helping next-gen AI systems accurately interpret advanced data patterns and logic flows.

Skills Required:

• Computer / Software / It / Data