Data Architect
5 days ago
Job Title: Data Architect
Job Summary: We are seeking a highly skilled Data Architect to lead the development of a cutting-edge data platform. The ideal candidate will have expertise in distributed computing frameworks and a strong understanding of cloud data platform architectures.
Key Responsibilities:
- Design and build a highly scalable, fault-tolerant data platform optimized for distributed computing and large-scale data processing.
- Implement data pipelines and ETL/ELT processes using distributed computing frameworks to efficiently ingest, transform, and load massive datasets from various sources.
- Leverage cloud data platforms to enable seamless data sharing, near-zero maintenance, and fast analytics on structured and semi-structured data.
- Collaborate with data scientists, machine learning engineers, and software developers to understand data requirements and build solutions to power GenAI applications.
- Optimize distributed computing jobs and queries for maximum performance and cost efficiency.
- Implement data governance, security, and compliance best practices.
- Provide guidance on distributed computing architecture and mentor junior data engineers.
Qualifications:
- 5+ years of experience as a Data Engineer working with big data technologies.
- Strong proficiency in SQL, Python programming, and data modeling techniques.
- Deep expertise in distributed computing principles and frameworks (e.g., Apache Spark), including SQL, streaming, and optimizing jobs for scale and efficiency.
- Hands-on experience with developing and deploying distributed computing applications using cloud-based platforms (e.g., AWS EMR, Azure HDInsight, or equivalent).
- Strong understanding of cloud data platform architectures and best practices for ELT/ETL, data sharing, and query optimization (e.g., AWS Athena, AWS Glue, Azure Synapse Analytics, or equivalent).
- Experience enabling application engineers to build applications leveraging the data platform through APIs and abstractions.
- Experience with orchestration frameworks like Apache Airflow and data streaming technologies like Kafka.
- Experience building and optimizing data pipelines for machine learning applications.
- Knowledge of data modelling, data warehousing, and schema design.
- Familiarity with public cloud platforms such as AWS, Azure, or GCP.
- Excellent problem-solving and communication skills.
Education: Bachelor's or Master's degree in Computer Science (Preferred), Engineering, or a related field.
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