Lead Data Engineer
New
A
Aker SystemsData Infrastructure
Remote/Home Based, UKFull-TimeLead
Salary not disclosed
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Job Details
- Required Skills
- AWSPythonSQLApache KafkaData engineeringCI/CDData modeling
Requirements
- Strong commercial experience designing and implementing real-time streaming data platforms.
- Hands-on experience with technologies such as Apache Kafka, AWS Kinesis, Apache Flink, Spark Streaming, or Apache Pulsar.
- Experience building high-volume, low-latency, resilient data pipelines in production environments.
- Extensive experience developing and operating enterprise-scale data platforms.
- Strong SQL skills and experience designing data models for analytical and operational workloads.
- Proficiency in Python or other modern programming languages used for data engineering.
- Strong experience working with AWS cloud services (EC2, RDS, Lambda, Athena, Glue, S3, IAM).
- Strong understanding of Test-Driven Development (TDD) and automated testing practices.
- Experience implementing CI/CD pipelines and engineering automation.
- Experience delivering technology solutions within UK Public Sector, Utilities, or other highly regulated industries.
Responsibilities
- Lead the design, development and deployment of secure, scalable data pipelines and data platform components.
- Design and implement batch and real-time streaming solutions using modern event-driven architectures.
- Own technical design decisions across projects, balancing scalability, security, performance and delivery requirements.
- Lead technical workshops, discovery sessions and architecture discussions with client stakeholders.
- Assess existing client data platforms and design practical approaches for modernisation, migration and integration.
- Build and maintain data ingestion, transformation and integration capabilities across a variety of data sources.
- Develop cloud-native data platforms using AWS services and open-source technologies.
- Ensure data quality, governance, lineage and security requirements are embedded throughout the data lifecycle.
- Drive engineering best practices including code reviews, automated testing, CI/CD and Infrastructure as Code.
- Mentor and support engineers across project teams, providing technical guidance and leadership.
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