Principal Software Engineer
Role details
Job location
Tech stack
Job description
A Global Media organisation is looking for a Principal Software Engineer to help provide strategic and technical leadership in the design, development, and governance of their enterprise-scale data infrastructure. This includes architecting and overseeing Data Lakes, Pipelines, and Data Products, ensuring solutions are scalable, secure, fault-tolerant, and high-performing. You will collaborate closely with multiple engineering teams and business stakeholders to align data engineering initiatives with enterprise data strategy and business goals. Your role will involve evaluating emerging technologies, driving automation and CI/CD practices, and implementing robust data governance, security, and privacy controls compliant with regulations such as GDPR. You will lead cross-functional teams, mentor engineers, and promote best practices in data modelling, quality, lineage, and observability.
This opportunity will also leverage AI and large language models to enhance data products and productivity which is why you will need a deep understanding of modern cloud-native data platforms, data mesh principles, and full software development lifecycle (SDLC) expertise, including system analysis, design, coding, integration, testing, and operations.
Requirements
- Enterprise data architecture and design (Data Lakes, Data Mesh, domain-oriented ownership)
- Data engineering and pipeline development (batch and Real Time processing)
- Cloud-native data services and infrastructure-as-code (AWS, Azure, GCP, Terraform, CloudFormation)
- Programming and Scripting (Python, SQL, C#)
- Data governance, metadata management, and compliance (GDPR, data cataloguing tools)
- AI and machine learning integration in data engineering
- Software development lifecycle (SDLC) expertise including quality assurance and delivery
- CI/CD and DevOps practices for data workflows
- Monitoring, alerting, and incident response for data infrastructure
- Leadership and mentoring of cross-functional engineering teams
Software/Tools:
- AWS S3, Azure Data Lake, Google Cloud Storage
- AWS Glue, Apache Spark, Kafka, SQS
- Azure Synapse, GCP BigQuery, Databricks
- Terraform, CloudFormation, Lakeformation
- Mixpanel, Power BI, Athena (product analytics tools)
- Collibra, Apache Atlas, OpenMetaData (data governance tools)
- Great Expectations, Monte Carlo (data quality frameworks)