[Hiring] Data Management and Analytics Engineer @Indotronix International Corporation

Role Description

Join our dynamic team as a Data Management and Analytics Engineer and drive the future of data-driven solutions. You'll work with modern cloud data platforms, engineer robust data pipelines, and collaborate with analytics and AI teams to shape innovative business outcomes. This is a remote, contract-to-hire opportunity designed for experienced professionals seeking impactful projects and growth in a collaborative environment.

Responsibilities

• Architect, build, and optimize scalable data pipelines using SQL, Python, ETL/ELT frameworks.
• Develop and maintain data solutions on Snowflake and leading cloud platforms.
• Implement data modeling, ensure high data quality, and manage metadata and data lineage.
• Integrate data sources via APIs and support both batch and real-time data processing.
• Utilize Git, CI/CD pipelines, and automated testing for seamless deployment.
• Collaborate with analytics, data governance, and AI teams to deliver trusted and actionable data solutions.

Qualifications

• 5-8+ years in data engineering, cloud data platforms, and enterprise data integration.
• Advanced proficiency in SQL, Python, ETL/ELT, and data modeling.
• Hands-on experience with Snowflake or similar cloud data platforms.
• Strong focus on data quality, metadata management, and data lineage.
• Practical knowledge of Git, CI/CD, and REST APIs.

Preferred Skills

• Familiarity with Kafka, Change Data Capture (CDC), dbt, Collibra, Ataccama, Power BI, AWS, OpenShift, and Kubernetes.
• Exposure to GenAI, Agentic AI, Retrieval-Augmented Generation (RAG), knowledge graphs, ontologies, and semantic models.

Benefits

• 100% remote work flexibility
• Contract-to-hire growth opportunity
• Collaborative, innovation-focused work environment
• Opportunity to work on cutting-edge analytics and AI initiatives

How to Apply

Ready to help shape the future of data management and analytics? Submit your resume today and take the next step in your data engineering career.