Data Engineering Manager - FMCG

Industry - Accounting / Finance / Audit

Category - Finance

Job Type - Permanent

Job Description - the person in this role will be required to work very closely with the data science team of D&A, along with partnering with the Data Engineering team. The person in this role will be required to demystify the ask of Data Science, bring out innovations in the space of Data Engineering by increasing the adoption of Data Science techniques, benefitting the Unilever Data Lake at large.

Client Details

Page Group are proud to be partnering with Unilever to support an ambitious global expansion on their Data & Analytical capabilities - investing further into technology for a sustainable, ethical and inclusive future. Unilever is one of the world's largest consumer goods companies, with sales in over 190 countries and reaching 2 billion consumers a day. Unilever has more than 400 brands found in homes around the world, including Persil, Dove, Knorr, Domestos, Hellmann's, Lipton, Wall's, PG Tips, Ben & Jerry's, Marmite, Magnum and Lynx. We are known for our great brands, a global footprint and our belief in doing business the right way."

Description

Key responsibilities of the role include:

- Spearhead the discussion and collaboration with D&A Data Science team.

- Work under the guidance of the Data Engineering leads to ensure the ask of the data science can be embedded into the data model of the Data Lake

- Model Data Quality assessment scenarios for not only showing the confidence in data but also, highlighting the areas for correction for quick correction

- Enable the ease of Data preparation and exploration

- Collaborate with enterprise architects, data architects, ETL developers & engineers, data scientists and information designers to lead identification and definition of required data structures, formats, pipelines, metadata, and workload orchestration capabilities.

- Address aspects around ML model build prerequisites for product(s), whilst incorporating the necessary activities required to be done by Data Engineers for sustainable future work

- Participate in deep architectural discussions to build confidence while building new solutions and migrating existing data applications on the Azure platform.

- Optimize data integration platform to provide optimal performance under increasing data volumes

- Create training contents wherever relevant

- Support the data architecture and data governance function to continually expand their capabilities

- Lead creation of design patterns for effective Data Engineering Practices across functions involving data science work loads

- Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools

- Work with business and application/solution teams to implement data strategies, lead build of data flows

- Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks

Key Accountabilities:

- Development of the Data Preparation Frameworks with best practice available in the market

- Development of solution which will enable "Model Ready Data" framework

- Development of Data Solutions in alignment with the Data Security and Data Governance Rules in various Markets (Countries)

- Development of Data Quality framework using advanced Machine Learning & Engineering techniques

- Develop a very good understanding of Unilever Data & Analytics Strategy and ensure alignment of team's priorities to the strategy

- Develop execution plan to enable future fit skills by training on Data Engineering principles

- Work closely with the D&A Markets, functions, Business teams, Geo IT and any spoke teams when it

comes to Data Engineering requirements

- Build and manage relationship with stakeholders within D&A and Business

- Drive operational excellence within the team

- Ensure adherence to SLA and drive user satisfaction

- Mentor team on continuous improvement which will includes Improved ways of working between

engagement, tracking, Simplification and Standardization

- Design thinking and Agile Scrum Approach

Profile

Experience and Qualifications Required:

Essential:

- 8 to 12 years of relevant experience in Data Science and Engineering

- Proficient in end-to-end Data Science Model development

- Working knowledge of Data Engineering tools and techniques

- Experience in developing data pipelines to transform, aggregate and or process data using Azure Databricks platform

- Experience in creating data pipelines using Azure Data Factory, Polybase and U-SQL or related tools on other cloud platform

- Experience of Working with Senior Business Stake holders.

Education:

Ideal candidates would preferably have a master's or Bachelor's degree in Computer Science

Job Offer

Rewards and benefits are just one part of the reason Unilever is a great place to work. We offer significant benefits, including a strong bonus, healthcare options, company share scheme, professional membership support and much more. In addition, there are a wide range of options around flexible working for the future. We offer a supportive and inclusive working environment that enables you to learn, develop and be the best you can in a role that suits you. We're committed to building an inclusive culture where everyone working at Unilever feels able to bring their complete and authentic self to work.

Page Group India is acting as an Employment Agency in relation to this vacancy.

Contact - Sanya Seth - +124 452 5520

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