Lead Data Engineer
2 weeks ago
About the Client: Our client are a tech for good business dedicated to promoting transparency in the corporate world they are seeking a highly skilled and experienced Lead Data Engineer.
You will be the first hire in the Data Engineering team allowing you to take the drivers seat regarding the direction taken by the data team to follow.
Key Responsibilities:
- Platform Development: Design, develop, maintain, test, and optimise a scalable and reliable data platform for collecting, processing, and transforming large volumes of company data from various sources.
- Collaboration: Work with cross-functional teams to understand data platform requirements and deliver solutions that meet business needs.
- Optimisation: Enhance data storage and retrieval systems for high performance and data integrity.
- Quality Assurance: Implement and maintain a data quality and observability framework to ensure data accuracy, completeness, and consistency.
- Documentation: Develop and maintain comprehensive documentation for data processes, schemas, and data dictionaries.
- Process Improvement: Identify and implement enhancements to improve data pipeline efficiency and reliability.
- Cloud Management: Actively manage cloud-based data services to balance performance and cost.
- Mentorship: Mentor and guide junior data engineers, fostering a culture of continuous learning and development.
- Innovation: Stay current with the latest data engineering technologies, tools, and best practices.
Required Technical Experience and Skillset:
- Educational Background: Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree is a plus.
- Experience: 8+ years in data engineering or a similar role.
Technical Skills:
- Advanced SQL skills and relational database management.
- Proficiency in at least two object-oriented programming languages (Python, Scala, Java).
- Deep familiarity with a cloud-native, modern data engineering technology stack compatible with AWS.
- Experience with web scraping and other data ingestion methods and tools.
- Knowledge of distributed computing frameworks (Hadoop, Spark, Hive, Presto).
- Experience with data orchestration tools (Airflow, Orchestra, Azkaban).
- Expertise in cloud data warehousing and core data modelling concepts.
- Proficiency in version control systems (Git) and experience with CI/CD pipelines.
- Project Management: Strong organisational and project management skills.
- Leadership: Proven ability to lead a data engineering platform implementation from scratch, working independently and as part of a team.
Preferred Experience and Skillset:
- Certifications: Data Engineering Certification is a plus.
- Database Design: Expertise in SQL and NoSQL databases (PostgreSQL, Cassandra, Elasticsearch).
- Stream Processing: Familiarity with stream processing technologies.
- Data Architecture: Deep understanding of data architecture considerations (data lakes, data warehouses, data lakehouses).
- AI/ML Integration: Experience deploying AI or machine learning models into production.
- Domain Knowledge: Experience with legal entity, UBO, or other datasets relevant to KYB/AML use cases.
Personal Attributes:
- Strong team fit and aptitude, with a focus on collaboration and problem-solving.
- Ability to trade ideas with peers to reach optimal solutions.
- Practical approach to incremental delivery of objectives.
- Capacity to balance perfection with the need for progress.
- Enthusiasm for solving complex problems at scale.
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