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 KafkaCI/CD
Requirements
- Strong commercial experience designing and implementing real-time streaming data platforms.
- Hands-on experience with Apache Kafka, AWS Kinesis, Apache Flink, Spark Streaming, Apache Pulsar or similar event-driven technologies.
- Experience building high-volume, low-latency, resilient data pipelines in production.
- 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 another modern programming language used for data engineering.
- Experience configuring, tuning and optimising relational and NoSQL databases.
- Strong experience with AWS services, including EC2, RDS, Lambda, Athena, Glue, S3 and IAM.
- Experience in Agile delivery environments, automated testing, CI/CD, Infrastructure as Code and Git.
- Experience delivering solutions in UK Public Sector, Utilities, Energy, Water, Financial Services or other regulated industries.
- Bachelor’s degree in computer science, Software Engineering, Data Engineering, Mathematics or a related technical discipline, or equivalent practical experience.
Responsibilities
- Lead the design, development and deployment of secure, scalable data pipelines and platform components.
- Design and implement batch and real-time streaming solutions using 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 client data platforms and design approaches for modernisation, migration and integration.
- Build and maintain data ingestion, transformation and integration capabilities across data sources.
- Develop cloud-native data platforms using AWS services and open-source technologies.
- Embed data quality, governance, lineage and security throughout the data lifecycle.
- Drive code reviews, automated testing, CI/CD and Infrastructure as Code practices.
- Mentor engineers and support delivery teams across multiple client engagements.
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