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- Tasks: Lead a team to build and optimise automated data pipelines using cutting-edge cloud technologies.
- Company: Join a forward-thinking company in Wimbledon, focused on innovative data solutions.
- Benefits: Enjoy flexible working options and opportunities for professional growth.
- Why this job: Be part of a dynamic team shaping the future of data engineering with real-world impact.
- Qualifications: Senior experience in Data Engineering, AWS, Databricks, and proficiency in Python and SQL required.
- Other info: Opportunity to mentor and lead a talented team while collaborating across departments.
The predicted salary is between 54000 - 84000 £ per year.
For this role, senior experience of Data Engineering and building automated data pipelines on IBM Datastage & DB2, AWS and Databricks from source to operational databases through to curation layer is expected using the latest cloud modern technologies where experience of delivering complex pipelines will be significantly valuable to how to maintain and deliver world class data pipelines.
Knowledge in the following areas essential:
- Databricks: Expertise in managing and scaling Databricks environments for ETL, data science, and analytics use cases.
- AWS Cloud: Extensive experience with AWS services such as S3, Glue, Lambda, RDS, and IAM.
- IBM Skills: DB2, Datastage, Tivoli Workload Scheduler, Urban Code.
- Programming Languages: Proficiency in Python, SQL.
- Data Warehousing & ETL: Experience with modern ETL frameworks and data warehousing techniques.
- DevOps & CI/CD: Familiarity with DevOps practices for data engineering, including infrastructure-as-code (e.g., Terraform, CloudFormation), CI/CD pipelines, and monitoring (e.g., CloudWatch, Datadog).
- Big Data Technologies: Familiarity with big data technologies like Apache Spark, Hadoop, or similar.
- ETL/ELT Tools: Creating common data sets across on-prem (IBM Datastage ETL) and cloud data stores.
- Leadership & Strategy: Lead Data Engineering team(s) in designing, developing, and maintaining highly scalable and performant data infrastructures.
- Customer Data Platform Development: Architect and manage our data platforms using IBM (legacy platform) & Databricks on AWS technologies (e.g., S3, Lambda, Glacier, Glue, EventBridge, RDS) to support real-time and batch data processing needs.
- Data Governance & Best Practices: Implement best practices for data governance, security, and data quality across our data platform. Ensure data is well-documented, accessible, and meets compliance standards.
- Pipeline Automation & Optimisation: Drive the automation of data pipelines and workflows to improve efficiency and reliability.
- Team Management: Mentor and grow a team of data engineers, ensuring alignment with business goals, delivery timelines, and technical standards.
- Cross Company Collaboration: Work closely with all levels of business stakeholders including data scientists, finance analysts, MI and cross-functional teams to ensure seamless data access and integration with various tools and systems.
- Cloud Management: Lead efforts to integrate and scale cloud data services on AWS, optimising costs and ensuring the resilience of the platform.
- Performance Monitoring: Establish monitoring and alerting solutions to ensure the high performance and availability of data pipelines and systems to ensure no impact to downstream consumers.
Big Data Lead employer: Falcon Smart IT (FalconSmartIT)
Contact Detail:
Falcon Smart IT (FalconSmartIT) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Big Data Lead
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as IBM Datastage, DB2, AWS, and Databricks. Having hands-on experience or relevant projects to discuss can set you apart during interviews.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who have experience with big data technologies like Apache Spark and Hadoop. Engaging in discussions on platforms like LinkedIn can help you gain insights and potentially get referrals.
✨Tip Number 3
Prepare to showcase your leadership skills and experience in managing teams. Be ready to discuss how you've successfully led data engineering projects and mentored team members, as this is a key aspect of the role.
✨Tip Number 4
Stay updated on best practices for data governance and security. Being knowledgeable about compliance standards and how to implement them will demonstrate your commitment to maintaining high-quality data infrastructures.
We think you need these skills to ace Big Data Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your senior experience in Data Engineering, particularly with IBM Datastage, DB2, AWS, and Databricks. Use specific examples of projects where you've built automated data pipelines and mention any relevant technologies you've worked with.
Craft a Strong Cover Letter: In your cover letter, emphasise your leadership skills and experience managing data engineering teams. Discuss how you have implemented best practices for data governance and pipeline automation, and how these experiences align with the company's needs.
Showcase Technical Skills: Clearly list your technical proficiencies in Python, SQL, and any big data technologies like Apache Spark or Hadoop. Mention your familiarity with DevOps practices and CI/CD pipelines, as these are crucial for the role.
Highlight Collaboration Experience: Demonstrate your ability to work cross-functionally by providing examples of how you've collaborated with data scientists, finance analysts, and other stakeholders. This will show that you can effectively integrate data access across various tools and systems.
How to prepare for a job interview at Falcon Smart IT (FalconSmartIT)
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with IBM Datastage, DB2, AWS, and Databricks in detail. Highlight specific projects where you built automated data pipelines and how you tackled challenges using these technologies.
✨Demonstrate Leadership Skills
As a Big Data Lead, you'll need to show your ability to lead and mentor a team. Share examples of how you've successfully managed teams, aligned them with business goals, and ensured timely delivery of projects.
✨Discuss Data Governance Practices
Familiarise yourself with best practices for data governance and security. Be ready to explain how you've implemented these practices in previous roles to ensure data quality and compliance.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about past experiences where you had to optimise data pipelines or integrate cloud services, and be ready to walk through your thought process.
