Senior Data Architect
4 weeks ago
Job Overview:
We are seeking a highly skilled Senior Data Engineer to join our team at AJ Consulting. As a Senior Data Engineer, you will play a crucial role in architecting and implementing our data infrastructure transformation. You will be responsible for converting complex, legacy data into structured, high-quality datasets that fuel AI and machine learning models.
Key Responsibilities:
- Legacy Data Transformation: Design and execute strategies to migrate and transform legacy data systems into modern, scalable architectures that are optimized for AI and ML workloads.
- Data Architecture & Modeling: Develop and maintain an efficient data architecture that supports real-time and batch processing, ensuring data integrity, security, and compliance.
- Platform Development: Work with modern data stack technologies (e.g., Hadoop, Spark, Kafka, AWS/Azure/GCP cloud services, SQL, NoSQL databases) to build and optimize data pipelines.
- AI/ML Enablement: Collaborate with data scientists and ML engineers to ensure data is properly formatted, cleaned, and enriched for AI model development and deployment.
- Performance Tuning: Optimize data processing pipelines for speed and efficiency, addressing bottlenecks and ensuring scalability.
- Data Governance: Implement and enforce data governance policies, including metadata management, data quality control, and data lineage tracking.
- Innovation & Best Practices: Stay abreast of emerging trends in data engineering and AI, introducing new tools and techniques to improve data infrastructure.
- Team Leadership: Mentor junior team members, fostering a culture of continuous learning and innovation.
Requirements:
- Education: Bachelor's or master's degree in computer science, Data Engineering, or a related field.
- Experience: A minimum of 7 years of hands-on experience in data engineering, with a focus on large-scale data migrations and transformations.
- Skills: Proficiency in programming languages such as Python, Java, or Scala. Extensive experience with big data technologies (Hadoop, Spark, Hive, HBase, etc.) and cloud-based data solutions (AWS S3, Azure Data Lake, GCP BigQuery). Strong understanding of database design, ETL processes, and data warehousing concepts.
- Soft Skills: Excellent problem-solving skills and ability to work collaboratively with cross-functional teams. Experience in data security, privacy, and GDPR/CCPA compliance. Strong communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.
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