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# Lead Data Integration Engineer

- **Company:** Kimberly Clark
- **Location:** Irving, TX, United States (Remote available)
- **Experience:** Expert
- **Salary:** $187,600.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Azure, Cloud Storage, Databases, Data as a Services, Data Integration, Extract Transform Load (ETL), Data Warehousing, Elasticsearch, Greenplum, Hadoop Distributed File System, Python (Programming Language), PostgreSQL, Metadata, Microsoft SQL Server, SQL Azure, MongoDB, NoSQL, Oracle (Applications), Redis, Standard Sql, SAP HANA, Teradata SQL, Data Processing, Google Cloud, Data Ingestion, Azure Data Factory, Snowflake, Apache Spark, Build Management, Sap Bo, Information Technology, Cassandra, Cosmos DB, Stream Analytics, Data Pipelines, Databricks
- **Published:** June 28, 2026
- **Apply:** https://www.dice.com/job-detail/6f0016c4-f925-4042-b2df-680f15350277

## About the Role

Requires a bachelor's or foreign equivalent degree in computer science, applied computer science, IT or a related field and 10 years of experience in the job offered or 10 years of experience designing, developing, and building ETL/ELT pipelines, procedures, and SQLs on MPP platforms including HANA, Snowflake, Greenplum, or Teradata. Also requires 5 years of experience: designing and building metadata driven data ingestion frameworks, building SAP BO/Data Services, Azure Data Factory, SnowSQL, and Snowpipe, and building mini-batch, real-time and event-driven data processing jobs; designing and developing object stores (including Azure ADLS, HDFS, and Google Cloud Platform Cloud Storage), Row and Columnar databases (including Azure SQL DW, SQL Server, Snowflake, Teradata, PostgresSQL, and Oracle), NoSQL databases (including CosmosDB, MongoDB, and Cassandra), ElasticSearch, Redis, and Data processing platforms Spark, Databricks, and SnowSQL; and leveraging Azure Stream Analytics, Azure

## Description

Lead Data Integration Engineer positions offered by Kimberly-Clark USA, LLC (Irving, Texas). Work with Technical Architects, Product Owners and Business teams to translate requirements into technical design for data modelling and data integration. Utilize 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. Review functional domain and business needs and 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.


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