Data Architect
3 weeks ago
About the Role
Duties & Responsibilities:
- Design and implement efficient data architectures, storage solutions, and data processing workflows, with a focus on stream processing, event queuing capabilities, and advanced CI/CD pipelines.
- Lead architecture design, development, and deployment of complex data-intensive systems using Kubernetes, data orchestration tools, distributed data processing frameworks, event queuing systems, and other modern technologies.
- Developing and maintaining accurate data models, data dictionaries, and data flow diagrams
- Collaborating with stakeholders to understand data requirements and translating them into technical specifications
- Performing data profiling and analysis to identify data quality issues and propose data cleansing and data integration solutions
- Implement and maintain robust security measures to protect sensitive data and ensure compliance with security standards and regulations
- Ensure the scalability, performance, and security of data-intensive systems, with a particular focus on stream processing, event queuing capabilities, and advanced CI/CD pipelines.
- Provide technical expertise and leadership to the project team, ensuring successful delivery of high-quality solutions on time and within budget.
- Stay current with emerging trends and technologies in data-intensive systems and provide thought leadership on best practices and solutions.
- Collaborate with sales and marketing teams to develop proposals and pitches that demonstrate our expertise in data-intensive systems, Kubernetes, data orchestration tools, distributed data processing frameworks, stream processing capabilities, event queuing systems, and advanced CI/CD pipelines.
Required Skills and Qualifications:
- 10+ years of experience in designing, implementing, and managing data-intensive systems.
- Expertise in data-intensive systems, including data architectures, storage solutions, and data processing workflows.
- Experience with Kubernetes and other container orchestration technologies.
- Experience with at least one data orchestration tool, such as Apache Airflow, Apache NiFi, Kedro, Stepfunction or Similar Technologies.
- Experience with at least one distributed data processing framework, such as Apache Spark, Apache Flink, Apache Beam or Similar Technologies.
- Very strong experience in stream processing, including real-time data processing, data ingestion, and data transformations.
- Experience with an event queuing system, such as Apache Kafka, AWS Kinesis, or Azure Event Hubs.
- Strong experience with cloud platforms such as AWS, Azure, or GCP.
- Advanced experience with CI/CD pipelines and tools such as Jenkins, GitLab, or CircleCI, including infrastructure as code, automated testing, and continuous monitoring.
- Excellent analytical and problem-solving skills.
- Strong leadership and communication skills with the ability to collaborate with cross-functional teams.
- Ability to work in a fast-paced, dynamic environment and manage multiple projects simultaneously.
Preferred Skills and qualifications
- Bachelor’s degree (or equivalent) in computer science, information technology, engineering, or related discipline
- Experience in building or maintaining ETL processes
- Professional certification
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