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Data Engineer Specialist
hace 1 mes
About Kimberly-Clark
We are a leading global healthcare company that offers a wide range of products and solutions to help people live healthier lives. Our team is passionate about making a difference in the world, and we are committed to delivering high-quality products and services that meet the needs of our customers.
At Kimberly-Clark, we value innovation, collaboration, and diversity. We believe that every individual has unique experiences and perspectives that contribute to the success of our organization.
About the Role
We are seeking an experienced Data Engineer who will play a key role in designing and implementing enterprise data solutions on cloud platforms. The ideal candidate will have a strong background in data engineering, cloud computing, and experience working with large-scale data systems.
The successful candidate will be responsible for developing and operationalizing 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.
In addition to technical skills, the candidate should possess excellent communication and collaboration skills, as they will work closely with cross-functional teams, including IT, business stakeholders, and data scientists.
Key Responsibilities:
- Design and implement enterprise data solutions on cloud platforms, ensuring scalability, security, and performance.
- Develop and maintain high-quality data pipelines for analytic solutions, automating data extraction, transformation, and loading (ETL) from various sources into centralized data warehouses or lakes.
- Manage and create data inventories for analytics and APIs, cataloging available data assets and their metadata, and ensuring accessibility and usability by various stakeholders.
- Collaborate with cross-functional teams, including IT, business stakeholders, and data scientists, to deliver high-quality data solutions that meet business requirements.
Required Qualifications:
- Bachelor's degree in management information systems/technology, Computer Science, Engineering, or related discipline. MBA or equivalent preferred.
- Minimum 5+ 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.
- 2+ 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.
- 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.
- 5+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
- 5+ years of experience with database development and scripting.
- Proficiency in creating data products that support analytic solutions, developing datasets, data models, and data services tailored to specific business needs.
- Proficiency in working with APIs and understanding data structures to serve them, designing, developing, and consuming APIs for data access and integration.
- Proficiency in programming languages such as SQL, NoSQL, Python, Java, R, and Scala, with 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, 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 based on specific use cases and data characteristics.
- 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.
- Basic understanding of big data tools such as Hadoop, MongoDB, and Kafka, experience in using big data technologies to manage, process, and analyze large datasets efficiently.
Estimated Salary: $120,000 - $150,000 per year
Benefits:
- Medical, dental, and vision coverage options with no waiting periods or pre-existing condition restrictions.
- Access to an on-site fitness center, occupational health nurse, and allowances for high-quality safety equipment.
- Flexible Savings and spending accounts to maximize health care options and stretch dollars when caring for yourself or dependents.
- Diverse income protection insurance options to protect yourself and your family in case of illness, injury, or other unexpected events.
- Additional programs and support to continue your education, adopt a child, relocate, or even find temporary childcare.
Location: Argentina-Buenos Aires, Sao Paulo Office
