Shape enterprise AI solutions and lead impactful data engineering projects. Collaborate in a hybrid environment with cutting-edge technologies. Drive innovation and optimize analytics workflows for enhanced decision-making.
Data And Integration Engineer
in Information Technology PermanentJob Detail
Job Description
Overview
- Drive innovation as a Data and Integration Engineer, shaping enterprise AI solutions and data workflows for impactful analytics.
- Collaborate with cross-functional teams to design and implement cutting-edge data integration systems.
- Utilize advanced technologies to automate data processes and optimize analytics pipelines.
- Contribute to projects that enhance decision-making through AI-driven insights and tools.
- Engage in a hybrid work environment, balancing flexibility with collaborative innovation.
- Stay ahead of industry trends by leveraging emerging technologies in AI and data engineering.
- Lead initiatives that transform complex data into actionable insights for enterprise applications.
- Contribute to a dynamic team focused on advancing AI analytics engineering practices.
Key Responsibilities & Duties
- Design and maintain robust data integrations across diverse enterprise systems.
- Develop workflows for efficient data extraction, transformation, and analytics automation.
- Implement AI-powered solutions for natural language data queries and insights.
- Automate testing, deployment, and monitoring of advanced analytics pipelines.
- Collaborate with stakeholders to deliver impactful and scalable data solutions.
- Document and share best practices for data reliability and process optimization.
- Prototype and scale AI-driven tools to enhance enterprise decision-making capabilities.
- Continuously explore and integrate emerging technologies in AI and data engineering.
Job Requirements
- Bachelor's degree in Computer Science, Data Engineering, or a related field.
- Minimum 7 years of experience in data engineering or systems integration.
- Proficiency in SQL, Python, and low-code integration tools.
- Experience with ETL/ELT workflows and enterprise system integrations.
- Knowledge of APIs, webhooks, and integration design patterns.
- Preferred experience with LLM frameworks and business intelligence tools.
- Strong communication skills for effective cross-functional collaboration.
- Familiarity with analytics engineering and data observability practices.
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