Senior Data Engineer

Senior Data Engineer

Join the team behind iconic brands like Huggies®, Kleenex®, Cottonelle®, Scott®, Kotex®, Poise®, Depend®, and Kimberly-Clark Professional® At Kimberly-Clark, it’s all here for you—innovation, growth, and the chance to make a real impact.

You were made to create Better Care for a Better World: designing new technologies, diving into data, optimizing digital experiences, and constantly developing better, faster ways to get results. You want to be part of a performance culture dedicated to building technology for a purpose that matters. Here, you’ll work in an environment that promotes sustainability, inclusion, wellbeing, and career development while you help us deliver better care for billions of people around the world. It starts with YOU.

About You

In one of our technical roles, you’ll focus on winning with consumers and the market, while putting safety, mutual respect, and human dignity at the center.

• Work with Technical architects, Product Owners, and Business teams to translate requirements into technical design for data modelling and data integration.
• Demonstrate deep background in data warehousing, data modelling and ETL/ELT data processing patterns.
• Design and develop ETL/ELT pipelines with reusable patterns and frameworks.
• Design and build efficient SQLs to process and curate the data sets in HANA, Azure, and Snowflake.
• Design and review data ingestion frameworks leveraging Python, Spark, Azure Data Factory, Snowpipe, etc.
• Design and build Data Quality models and ABCR frameworks to ingest, validate, curate, and prepare the data for consumption.
• Understand the functional domain, business needs and able to identify the gaps in the requirements proactively prior to implementing solutions.
• Work with platform teams to design and build processes for automation in pipeline build, testing and code migrations.
• Collaborate with Data Scientists to build and maintain scalable pipelines in Azure Data Factory and Databricks that support AI/ML modelling and model training workflows.
• Support the integration of Generative AI by building robust pipelines for high-quality training data and implementing vector databases to power Retrieval-Augmented Generation (RAG) workflows.
• Demonstrate exceptional impact in delivering projects, products and/or platforms in terms of scalable data processing and application architectures, technical deliverables, and delivery throughout the project lifecycle.
• Provide design and guiding principles on building data models and semantic models in Snowflake – enabling true self-service.
• Responsible for ensuring the effectiveness of the ingestion and data delivery frameworks and patterns.
• Build and maintain data development standards and principles, provide guidance and project specific recommendations as appropriate.
• Must be conversant with DevOps delivery approach and tools and have a track record of delivering products in agile model.
• Provide insight and direction on roles and responsibilities required for platform/ product operations.

Required Qualifications

• 5+ years of experience designing, developing, and building ETL/ELT pipelines, procedures, and SQLs on MPP platforms such as HANA and Snowflake.
• 5+ years of experience in Data warehousing and Business Intelligence.
• Experience in Data Warehousing concepts like Star schema, Snowflake schema, Fact table and Dimension Table.
• Experience in using various features of ADF to load data into snowflake.
• Experience in designing and building metadata driven data ingestion frameworks, building Azure Data Factory, SnowSQL, Snowpipe – as well as building mini-batch, real-time and event-driven data processing jobs.
• Hands-on experience with Azure.
• Familiarity in leveraging Azure Stream Analytics, Azure Analysis Services, Data Lake Analytics, HDInsight, HDP, Spark, Databricks, MapReduce, Pig, Hive, Tez, SSAS, Watson Analytics, SPSS.
• Strong Knowledge on source code management, configuration management, CI/CD, security, and performance.
• Ability to look ahead to identify opportunities and thrive in a culture of innovation.
• Self-starter who can see the big picture, and prioritize your work to make the largest impact on the business’ and customer’s vision and requirements.
• Experience in building, testing, and deploying code to run on Azure cloud data lake.
• Ability to Lead/nurture/mentor others in the team.
• A can-do attitude in anticipating and resolving problems to help your team to achieve its goals.
• Must have experience in Agile development methods.

Preferred Qualifications

• Foundational understanding of AI/ML modelling concepts and experience integrating data with Azure Machine Learning services for model deployment and tracking.
• Foundational understanding of GenAI concepts, including the data requirements for Large Language Models (LLMs) and basic familiarity with Azure OpenAI Service.
• Knowledge of Change Data Capture on both Source and Target, and implementation of the SCD (Slowly changing Dimension) Type 1, Type 2, and Type 3.
• Experience in modelling data warehouse in Snowflake.
• Experience in Azure logic apps and power automate.
• Proficient in distributed computing principles, modular application architecture, and various types of data processing patterns – real-time, batch, lambda, and other architectures.
• Experience with a broad range of data stores - Object stores (Azure ADLS, HDFS, GCP Cloud Storage), Row and Columnar databases (Azure SQL DW, SQL Server, Snowflake, Teradata, PostgreSQL, Oracle), NoSQL databases (Cosmos DB, MongoDB, Cassandra), Elasticsearch, Redis, and Data processing platforms – Spark, Databricks, and SnowSQL.

Key skills/competency

• Data Engineering
• ETL/ELT
• Data Warehousing
• SQL
• Python
• Spark
• Azure Data Factory
• Snowflake
• Data Modeling
• Generative AI