Play a key role in scaling and improving how we integrate and process customer data by designing and implementing ETLs that reliably process large volumes of customer-provided data and build tools to make customer integrations faster. Your work will have a direct and visible impact on our ability to onboard customers easier and quicker and power our machine learning grocery solution.

You will lead the design, development, and implementation of data-centric solutions to drive actionable insights and enhance decision-making processes. You will collaborate with cross-functional teams to architect scalable and efficient data pipelines, optimize data storage and retrieval systems, and ensure data quality and integrity throughout the data lifecycle.

Design, develop, and maintain scalable data pipelines using Python, Spark, and Databricks. Integrate data from various sources into a unified data warehouse, ensuring data quality and governance. Optimize Spark jobs, implement CI/CD pipelines, and collaborate with stakeholders to deliver data solutions.

Work with business to understand, analyze, and blueprint business functional needs in the system. Design new solutions using Databricks and Qlik to deliver capabilities meeting business functional requirements. Build data models and reports using datasets from ERP’s and legacy systems.

Lead the design, architecture, and implementation of large-scale data solutions for clients. Act as a strategic technical leader, collaborating with cross-functional teams to deliver innovative data platforms that drive business value. Define and drive technical strategies that align AWS capabilities with customer objectives, incorporating Databricks, GCP, or Azure where appropriate.

The Sr. Manager will lead a team of data engineers and data scientists that will collaborate with business leaders to design and implement business process automations and advance projects and strategic deliverables for External Supply Operations. Duties include strategic planning, collaboration with IT, mentoring, and optimizing infrastructure.

As an Analytics Manager, you will create a next generation analytics platform, enabling the company to monitor and analyze business leading to sustainable and disciplined business outcomes. This involves maintaining analytical environments, building data solutions, setting the vision for analytics use, and leading a team of analytics engineers.

The Senior Data Engineer role requires at least 6 years' experience and solid knowledge of Azure. Strong skills in Databricks, DBT, Fivetran, and Airflow are essential, as is experience in an agile environment and good English knowledge.

At the forefront of our AI and Machine Learning innovation! You'll design and deploy machine learning, deep learning, and LLM models that will shape our customer experience, drive business growth, and improve operational efficiency while collaborating closely with product, engineering, and analytics teams. Passionate about using AI to solve real-world problems at scale.

Expand and improve the data and data pipeline architecture, as well as optimizing data flow and MDM for cross-functional teams. Design, develop, and operate large-scale data pipelines to support internal and external consumers. Integrate data sources to meet business requirements. Write robust, maintainable, well-documented code.