Data Lead – Palantir experience + Python, PySpark, SQL, Big Data
12 Months initial contract
Hybrid (Maidenhead) – 2 days onsite per week
Inside IR35
My client a top Global company are currently looking to recruit a Data Lead with Palantir experience to join their team on a contract basis. Please note if successful you will need to set up via an Umbrella Company/PAYE. The Data Lead will direct all data resources (analysts and engineers) to manage operational, tactical, and strategic data focused activities. The role will assure operational capability to support business critical activities, enhance and strengthen portfolio ambitions, administer resource workloads, and resource performance against business priorities. Strategically the Data Lead will be setting the vision and executing the UK Data Strategy, seek key improvements to current processes, improve data capabilities through constantly evolving our offering to scale our capability with the growth of the business and the needs of our customers and increase the data maturity of the affiliate supporting advanced analytics capabilities.
Key responsibilities
- Data Strategy : define and drive the long-term vision to underpin the affiliates ambitions of a significantly increased portfolio delivered through an omni-channel lens, which will fundamentally revolutionise the way we deliver to our customers and ultimately patients.
- Data Management/Governance: producing the right activities and processes around data to ensure data is properly managed in the business, through:
- Data Standards and Quality
Improving data quality: take full ownership for ensuring that our data meets corporate standards for quality. Ensuring the data value and data risk needs are met. Managing data quality standards where required. Accountable for producing production-strength data pipelines and solutions.
- Data Architecture : Developing and enabling the framework on how the infrastructure supports the data strategy.
- Master Data Management: Accountable to creating a technology-enabled discipline where there is uniformity, accuracy, stewardship, semantic consistency across shared master data assets.
- Data Security and Compliance: working with cross functional teams to guard against intrusion, corruption, and loss of data. Build strong data governance and data protection practices.
- Data Accessibility: mitigate any bottlenecks in accessing data, provide effective access to enterprise information, while also balancing the free flow of data (with the necessary safeguards). Educate the business to ensure data needs are met in an effective and robust way.
- Resource Planning: Setting of backlog priorities based on stakeholder feedback. Manage release cycle plans inline with the business needs and team coordination and support of sprint progress. Ensure the facilitation of daily sprint initiatives, enabling the communication between the team and stakeholders, providing coaching, handling administrative tasks, and shielding the team from external interferences during sprints.
- Building a data culture : evolve and mature mindsets and working practices relating to data across all levels of the organisation.
- Advancing data and analytics maturity: In conjunction with the Business Analytics team, ensuring that our client is consistently using data analytics to spark innovation that differentiates our business, supports our strategic priorities, and drives competitive advantage.
- Data Engineering : Engages internally and externally to keep informed and promotes the use of latest technology and tools. Responsible for data ingestion, automation, and quality control. Responsible for testing, error handling and resolution. Management of the data architecture, data platforms, reporting and analytics platforms. Accountable for the technical standards and knowledge sharing sessions.
- Stakeholder Engagement : As a member of the Data and Analytics governance team, prioritises projects to deliver the most value. Ensuring a very close working relationship with Customer Excellence functions (Local, WEC and Global), Finance and commercial functions to ensure strategic alignment across the business.
- Team Management: Accountable for managing all data engineers and analyst including setting team strategy, staff developing, hiring, retention planning and general line management responsibilities.
Qualifications & Competencies
- A desire to work in a collaborative, intellectually curious environment.
- Experience mentoring and managing other Data Engineers/Analysts, ensuring data engineering best practices are being followed.
- Experience in maintaining data warehouse systems and working on large scale data transformation, and knowledge of at least one MDM.
- Development skills – experience using Python, PySpark, SQL, Big Data experience (Palantir) and DataOps.
- Certified Data Management Professional and TOGAF.
- Interpersonal skills and the ability to communicate complex technology solutions to senior leadership, gain alignment, and drive progress.
- Experience of architecture methodologies, principles, and frameworks.
- Data Management best practice, including Data Lifecycle Management across Core IT & Big Data ecosystems as well as Data Privacy & Security constraints.
- Knowledge and previous experience in Data Modelling.
- A good level of knowledge of enterprise CRM systems (such as Veeva) and analytical dashboarding systems (such as QlikSense).
