Data Specialist

Key Skills

AWS, Azure, Data Engineering, Data science techniques, Data Visualization, ETL frameworks, Google Cloud Platform (GCP), Machine learning techniques, PowerBI, PySpark, Python Programming, SQL, Tableau

Job Description

As a Data Engineer, you will be responsible for designing, building, and managing the data environment that extracts, cleans, secures, integrates, transforms, and delivers data for business consumption. You will work closely with the Data Science team to ensure that our data is clean, accurate, and accessible.

Responsibilities:

• Designing and implementing scalable data pipelines required to support a use case or customer request.

• Developing and maintaining ETL processes to move data from various systems to our data warehouse.

• Creating data models and business views that present data in a user-friendly schema.

• Tracking and managing data quality, making changes and fixes as needed.

• Installing, configuring, managing, and upgrading data management systems.

• Managing database security and tuning database performance.

Qualifications:

• Bachelor's degree in Computer Science, Data Science, or related field.

• 2+ years of experience in data engineering or related field.

• Strong programming skills in Pyspark, Python and SQL.

• Experience working with cloud-based data technologies such as AWS, GCP, or Azure, including Microsoft Azure Storage Explorer and Databricks.

• Strong understanding of data modeling and database design principles.

• Knowledge of API integrations and setting up future-proof data infrastructures in line with the business strategy.

• Familiarity with Agile development methodologies.

• Excellent problem-solving and analytical skills.

• Strong communication and collaboration skills to deploy all business requirements in line with the strategy. Ability to explain the data in a super simple way to stakeholders in the company and understand their business needs.

• Fluent English communication skills, verbal and written.

• Results-driven, with the ability to create streamlined data warehouses and basic reporting that is accessible, usable, and highly focused on delivering insights.

• Team player that can work cross-functionally with marketing and data technology teams.

Preferred Qualifications:

• Experience working in a fast-paced, dynamic environment.

• Experience with data visualization tools such as Tableau or Power BI.

• Familiarity with machine learning and data science concepts.

• Building integrations with third-party tools and services.

Collaborating with other teams to identify data needs and help them use data to build complex data pipelines and help deploy analytic models into production applications, including enterprise reports and real-time customer-facing applications.

Keeping up-to-date with the latest trends and technologies in data engineering and recommending improvements to our data infrastructure.

Work with team to deploy analytic models into production applications, including enterprise reports and real-time customer-facing applications.

Unilever is an organisation committed to equity, inclusion and diversity to drive our business results and create a better future, every day, for our diverse employees, global consumers, partners, and communities. We believe a diverse workforce allows us to match our growth ambitions and drive inclusion across the business. At Unilever we are interested in every individual bringing their ‘Whole Self’ to work and this includes you! Thus if you require any support or access requirements, we encourage you to advise us at the time of your application so that we can support you through your recruitment journey.