At a Glance
- Tasks: Transform data into robust solutions for key stakeholders using SQL, Python, and Power BI.
- Company: Join PMI, a leader in smoke-free products, committed to innovation and positive change.
- Benefits: Enjoy flexible work options, mental health support, and a culture of inclusion and belonging.
- Why this job: Make a life-changing impact while developing your career in a dynamic, supportive environment.
- Qualifications: 8+ years of experience in data architecture, strong SQL and Python skills required.
- Other info: Be part of a diverse team with a commitment to equality and employee wellbeing.
The predicted salary is between 43200 - 72000 £ per year.
Be a part of a revolutionary change\’
About us
At PMI we\’ve chosen to do something incredible. We\’re totally transforming our business and building our future on smoke-free products.
With huge change comes huge opportunity. So, wherever you join us, you\’ll enjoy the freedom to dream up and deliver better, brighter solutions and the space to move your career forward in endlessly different directions.
If you want to make a life-changing impact on Customers, there\’s nowhere better to develop your career.
Main Purpose of Role
The role is crucial in transforming data by bridging data warehousing and business analysis into robust data solutions for analytical consumption for key stakeholders. The role will be responsible for working to build out and improve the company\’s data ingestion, transformation, transactional and data warehousing needs directly supporting the data science and analyst teams.
This role is essential to building and scaling new and existing local data streams to support PML\’s growing data products and services. In addition to this, the role will review and redesign product to address resource heavy processes.
Partnering with the Manager Data Capability and Head of Data and Analytics, the role will be working on varying, complex projects that leverages expertise in Power BI, to help the organisation harness the power of cloud technologies available to PMI such as Amazon Web Services (AWS), Matillion and Snowflake.
The role will also work with market LT in order to understand the business strategy and therefore design data products to serve the strategy.
The role is autonomous and therefore requires someone who can bring solutions to problem statements around data.
Responsibilities
Data Modeling & Warehousing :
Design, develop, and maintain scalable data models and ensure the data warehouse is consistent and future-proof.
Data Pipelines :
Develop reliable data pipelines to ensure seamless data flow, considering data lineage and optimization.
Perform database tuning and optimization for improved query performance.
Data Integration :
Use ETL tools, SQL, and Python to integrate external datasets into the data warehouse.
Data Quality & Security :
Implement data quality checks and ensure compliance with data protection regulations.
Performance Optimization :
Enhance data storage and retrieval processes for better performance and scalability.
Data Governance :
Apply data governance principles, including metadata management and documentation.
Drive best practices and ensure the data platform meets business needs.
Collaboration :
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and design tailored data solutions.
Collaborate with IT to align projects with infrastructure and policies.
Documentation :
Maintain comprehensive documentation of data models and processes.
Business Translation :
Convert business logic into data products and actionable insights.
Stakeholder Engagement
Engage with global stakeholders to understand the impact of global changes on local data.
Partner with market LT to align data design to market strategy.
Enterprise Data Analytics:
Engage and adhere to enterprise data analytics guidelines and utilize appropriate tooling.
Skills, Experience and Competencies Required
8 years+ SME experience
Strong skills in data architecture and pipeline development, with extensive experience in SQL and Python; PowerBI knowledge is a plus.
Experience with ETL/ELT tools (e.g., Matillion, DBT).
Strong understanding of data warehouse engineering and architecture principles.
Additional Role Requirements
Stay updated with industry trends to improve data engineering practices.
Our commitment to inclusion
PMI is on a continuous journey to ensure that all of our employees feel welcome and feel that they belong.
We have a number of internal networks that are inclusive and open for anyone to join, including networks covering employees from ethnic minority backgrounds, LGBTQ+ and gender. We\’re also extremely proud to be the first global company to be awarded Equal Salary Certification.
We take wellbeing seriously, so we have trained mental health First Aiders to help support our employees, as well as support in the form of our LifeWorks app and Employee Assistance Program.
PMI is an equal opportunities employer, hiring solely on merit and business need. We encourage applications regardless of sex, gender identity, ethnicity, age, sexual orientation, gender reassignment, religion or belief, marital status, pregnancy, parenthood and disability. If you require reasonable adjustments in any recruitment process with us, please make us aware.
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Analytics Data Engineer employer: Philip Morris International
Contact Detail:
Philip Morris International Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Power BI, AWS, Matillion, and Snowflake. Having hands-on experience or projects showcasing your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Network with current employees or professionals in the data engineering field, especially those who work at PMI. Engaging in conversations about their experiences can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Stay updated on the latest trends in data engineering and analytics. Being able to discuss recent advancements or best practices during interviews can demonstrate your commitment to continuous learning and improvement.
✨Tip Number 4
Prepare to discuss how you've successfully collaborated with stakeholders in previous roles. Highlighting your ability to translate business needs into data solutions will resonate well with the responsibilities outlined in the job description.
We think you need these skills to ace Analytics Data Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure to thoroughly read the job description for the Analytics Data Engineer position. Understand the key responsibilities and required skills, such as data modelling, ETL tools, and collaboration with stakeholders.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job requirements. Emphasise your expertise in SQL, Python, and any experience with Power BI or ETL tools like Matillion.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and how your background makes you a perfect fit for the role. Mention specific projects or achievements that demonstrate your ability to deliver data solutions.
Highlight Soft Skills: In addition to technical skills, emphasise your soft skills such as problem-solving, collaboration, and communication. These are crucial for engaging with stakeholders and translating business needs into data products.
How to prepare for a job interview at Philip Morris International
✨Showcase Your Technical Skills
Make sure to highlight your expertise in SQL, Python, and any ETL tools you've used, such as Matillion or DBT. Be prepared to discuss specific projects where you developed data pipelines or optimised data models.
✨Understand the Business Context
Familiarise yourself with PMI's smoke-free product transformation and how data engineering supports this initiative. Demonstrating an understanding of the company's strategy will show that you're aligned with their goals.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your ability to solve complex data challenges. Think of examples where you've successfully addressed data quality issues or improved data flow, and be ready to explain your thought process.
✨Emphasise Collaboration Skills
Since the role involves working closely with data scientists and analysts, be sure to discuss your experience collaborating with cross-functional teams. Highlight any instances where you translated business needs into actionable data solutions.