YOUR JOB

You’re not the person who will settle for just any role. Neither are we. Because we’re out to create Better Care for a Better World, and that takes a certain kind of person and teams who care about making a difference. Here, you’ll bring your professional expertise, talent, and drive to building and managing our portfolio of iconic, ground-breaking brands. In your role, you’ll help us deliver better care for billions of people around the world. It starts with YOU.

ABOUT US

Huggies®. Kleenex®. Cottonelle®. Scott®. Kotex®. Poise®. Depend®. Kimberly-Clark Professional®. You already know our legendary brands—and so does the rest of the world. In fact, millions of people use Kimberly-Clark products every day. We know these amazing Kimberly-Clark products wouldn’t exist without talented professionals, like you.
At Kimberly-Clark, you’ll be part of the best team committed to driving innovation, growth and impact. We’re founded on 150 years of market leadership, and we’re always looking for new and better ways to perform – so there’s your open door of opportunity. It’s all here for you at Kimberly-Clark; you just need to log on!
Led by Purpose. Driven by You.

REQUIRED SKILLS AND EXPERIENCE:

• Deep understanding of data architecture, data engineering, data warehousing, data analysis, reporting, and data science techniques and workflows: You should have a comprehensive knowledge of designing and implementing data systems that support various analytic and operational use cases, including data storage, processing, and retrieval.
• SAP HANA: Ability to analyze current models and also migrate data and models from SAP HANA into Snowflake environment, ensuring seamless data flow and consistency across platforms.
• Skilled in creating data products that support analytic solutions: Proficiency in developing data products that enable stakeholders to derive meaningful insights and make data-driven decisions. This involves creating datasets, data models, and data services tailored to specific business needs.
• Proficiency in working with APIs and understanding data structures to serve them: Experience in designing, developing, and consuming APIs for data access and integration. This includes understanding various data structures and formats used in API communication.
• Experience with Object-Relational Mapping (ORM) frameworks: Familiarity with ORM frameworks, such as Hibernate or Entity Framework, to efficiently map data between relational databases and application code.
• Knowledge of managing sensitive data, ensuring data privacy and security: Expertise in handling sensitive data with strict adherence to data privacy regulations and security best practices to protect against unauthorized access and breaches. Working knowledge for developing secure and governed solutions on cloud computing services and infrastructure in the data and analytics space (Azure, AWS or GCP). Knowledge of Snowflake Row Level Security (RLS)
• Strong problem-solving skills and ability to work as part of a technical, cross-functional analytics team: Excellent analytical and troubleshooting abilities, with the capability to collaborate effectively with team members from various technical and business domains.
• Experience with relational and non-relational databases (NoSQL, graph databases, etc.): Solid experience in working with different types of databases, including traditional relational databases (e.g., Snowflake, SQL Server, MySQL) and non-relational databases (e.g., MongoDB, graph databases).
• Agile learner with a passion for solving complex data problems and delivering insights: A proactive and continuous learner with enthusiasm for addressing challenging data issues and providing valuable insights through innovative solutions.
• Proficiency in programming languages such as SQL, NoSQL, Python, Java, R, and Scala: Strong coding skills in multiple programming languages used for data manipulation, analysis, and pipeline development.
• Experience with ETL (extract, transform, and load) systems and API integrations: Expertise in building and maintaining ETL processes to consolidate data from various sources into centralized repositories, and integrating APIs for seamless data exchange.
• Understanding of data storage solutions, knowing when to use a data lake versus a data warehouse: Knowledge of different data storage architectures and the ability to choose the appropriate solution (data lake or data warehouse) based on specific use cases and data characteristics.
• Ability to write scripts for automation and repetitive task management: Proficiency in scripting languages (e.g., Python, Bash) to automate data processing tasks and reduce manual efforts.
• Basic understanding of machine learning concepts to support data scientists on the team: Familiarity with key machine learning principles and techniques to better collaborate with data scientists and support their analytical models.
• Proficiency with big data tools such as Snowflake, Kafka, Azure EventHub, IoT Hub: Experience in using big data technologies to manage, process, and analyze large datasets efficiently.
• Knowledge of cloud computing, including cloud storage, product portfolios, and pricing models (Azure): Understanding of cloud platforms and services, particularly Azure, including storage options, available tools, and cost considerations.
• Azure cloud services (or equivalent cloud) experience with tools like Azure Data Factory, Databricks, Integration Runtime Services, Azure Functions and Azure Logic Apps
• Performance Tuning: Optimize the performance of data pipelines and queries in both Azure and Snowflake environments.

KNOWLEDGE AND EXPERIENCE

• Bachelor’s degree in management information systems/technology, Computer Science, Engineering, or related discipline. MBA or equivalent is preferred.
• Minimum 10+ years of experience in designing large-scale data solutions, performing design assessments, crafting design options and analysis, finalizing preferred solution choice working with IT and Business stakeholders.
• 5+ years of experience tailoring, configuring, and crafting solutions within the Snowflake environment, including a profound grasp of Snowflake’s data warehousing capabilities, data architecture, SQL optimization for Snowflake, and leveraging Snowflake’s unique features such as Snowpipe, Streams, and Tasks for real-time data processing and analytics. A strong foundation in data migration strategies, performance tuning, and securing data within the Snowflake ecosystem is biessential.
• 3+ years demonstrated expertise in architecting solutions within the Snowflake ecosystem, adhering to best practices in data architecture and design patterns.
• 10+ years of data engineering or design experience, designing, developing, and deploying scalable enterprise data analytics solutions from source system through ingestion and reporting.
• Expertise in data modeling principles/methods including, Conceptual, Logical & Physical Data Models for data warehouses, data lakes and/or database management systems.
• 5+ years of hands-on experience designing, building, and operationalizing data solutions and applications using cloud data and analytics services in combination with 3rd parties.
• 10+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
• 10+ years of experience with database development and scripting.
• Experience introducing and operationalizing self-service data preparation tools (e.g. Collibra, Alation, Babylon).
• Additional technology accentuators include working knowledge of SAP ERP data and structures, SAP HANA.
• Cloud Certified Professional Data Engineer preferred.
• Experience with large manufacturing CPG is preferred.
• Experience working with retailer data (e.g. POS, Inventory) and Syndicated data (e.g. Nielsen, Profitero) preferred.

PROFESSIONAL SKILLS:

• Strong leadership and management skills.
• Strong communication and interpersonal skills.
• Strong analytical and problem-solving skills and passion for product development.
• Strong understanding of Agile methodologies and open to working in agile environments with multiple stakeholders.
• Professional attitude and service orientation; team player.
• Ability to translate business needs into potential analytics solutions.
• Strong work ethic: ability to work at an abstract level and gain consensus.
• Ability to build a sense of trust and rapport to create a comfortable and effective workplace.

MAIN RESPONSIBILITIES:

Our Cloud Data Engineers play a crucial role in designing and operationalizing transformational enterprise data solutions on Cloud Platforms, integrating Azure services, Snowflake technology, and other third-party data technologies. Cloud Data Engineers will work closely with a multidisciplinary agile team to build high-quality data pipelines that drive analytic solutions. These solutions will generate insights from our connected data, enabling Kimberly-Clark to advance its data-driven decision-making capabilities.
The ideal candidate will have a deep understanding of data architecture, data engineering, data warehousing, data analysis, reporting, and data science techniques and workflows. They should be skilled in creating data products that support analytic solutions and possess proficiency in working with APIs and understanding data structures to serve them. Experience with ORM frameworks and knowledge of managing sensitive data, ensuring data privacy and security, are essential. The candidate should have strong problem-solving skills, be able to work as part of a technical, cross-functional analytics team, and be an agile learner with a passion for solving complex data problems and delivering insights.
If you are an agile learner, possess strong problem-solving skills, can work as part of a technical, cross-functional analytics team, and want to solve complex data problems while delivering insights that help enable our analytics strategy, we would like to hear from you.
This role is perfect for a developer passionate about leveraging cutting-edge technologies to create impactful digital products that connect with and serve our clients effectively. (Kimberly-Clark Corporation) has an amazing opportunity to continue leading the market, and DTS is poised to deliver compelling and robust digital capabilities, products, and solutions to support it. This role will have substantial influence in this endeavor.
If you are excited to make a difference applying cutting-edge technologies to solve real business challenges and add value to a global, market-leading organization, please come join us!

KEY RESPONSIBILITIES:

• Design and operationalize enterprise data solutions on Cloud Platforms: Develop and implement scalable and secure data solutions on cloud platforms, ensuring they meet enterprise standards and requirements. This includes designing data architecture, selecting appropriate cloud services, and optimizing performance for data processing and storage.
• Integrate Azure services, Snowflake technology, and other third-party data technologies: Seamlessly integrate various data technologies, including Azure services, Snowflake, and other third-party tools, to create a cohesive data ecosystem. This involves configuring data connectors, ensuring data flow consistency, and managing dependencies between different systems.
• Build and maintain high-quality data pipelines for analytic solutions: Develop robust data pipelines that automate the extraction, transformation, and loading (ETL) of data from various sources into a centralized data warehouse or lake. Ensure these pipelines are efficient, reliable, reusable when possible and capable of handling large volumes of data.
• Collaborate with a multidisciplinary agile team to generate insights from connected data Work closely with data scientists, analysts, and other team members in an agile environment to translate business requirements into technical solutions. Participate in sprint planning, stand-ups, and retrospectives to ensure timely delivery of data products.
• Manage and create data inventories for analytics and APIs to be consumed: Develop and maintain comprehensive data inventories that catalog available data assets and their metadata. Ensure these inventories are accessible and usable by various stakeholders, including through APIs that facilitate data consumption.
• Design data integrations with internal and external products: Architect and implement data integration solutions that enable seamless data exchange between internal systems and external partners or products. This includes ensuring data integrity, security, and compliance with relevant standards.