Data Engineering Lead
3 weeks ago
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- We have a new and exciting opportunity for a Data Engineering Lead to join our newly created Group Technology function. Working closely and supporting the Chief Information & Data Officer you will lead the delivery of a Datalake for the global business and building data pipelines, that support commercial data propositions we sell to our customer and deliver data to your internal stakeholders to manage business performance. You will engage with Product managers and stakeholders both internally and externally, to focus on revenue growth and enhance decision making through the ‘Power of Data’.
- You will be adapt at managing C-Suite stakeholders, have a commercial data mindset, establishing strategies and methods covering all data use cases, Insights, Streaming, product integration/orchestration, Data science and multi-tenant architectures.
Key Responsibilities:
Duties include:
- Define and implement the strategic data architecture for the business
- Create and manage the delivery roadmap for Data engineering
- Design, develop, and maintain scalable data pipelines and ETL processes using Databricks.
- Write efficient and optimized SQL queries for data extraction and transformation.
- Develop and maintain data integration workflows using Python, Scala, and Java/React
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
- Ensure data quality and integrity through rigorous testing and validation.
- Monitor and troubleshoot data pipeline performance and reliability.
- Implement best practices for data management, security, and governance.
- Stay up-to-date with the latest industry trends and technologies in data engineering.
- Implementing plans to educate the organisation on the ‘Power of Data’
- Confidently talk to external customers and business events, about how KCS unleashes the power of data for its growth
- Lead and grow a team of expert data engineers
Skills, Knowledge and Experience:
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineering or in a similar role.
- Proficiency in Databricks, SQL, Python, Scala, and Java, Oracle, Pyspark
- Experience in building Graph, Vector, NoSQL and data lakehouse architectures
- Strong understanding of data warehousing concepts and ETL processes.
- Experience with on-premise and cloud platform architectures (AWS, Azure and Oracle Cloud)
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills.
- Ability to work in a fast-paced, dynamic environment.
- Outstanding verbal and written communication skills
- Excellent interpersonal and organisational skills
- Strong commercial awareness in all areas
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