Sr. Specialist , Data Engineering

Brief introduction - Role Summary/Purpose: 

Colgate-Palmolive is looking for a Sr. Specialist Data Engineer to join its growing Global Information Technology organization. The Sr. Specialist, Data Enginer will work closely with the discrete business areas, as well as the Global Information Technology functional organizations across the globe.

The successful candidate will be managing and developing the solution which entails planning, design, development and maintenance of our data repositories, pipeline and analytical solutions. The ideal candidate is self driven and looking to build high quality tools to deliver actionable insights to our business partners to facilitate data-driven decision making. The candidate needs to be a self-starter - eager to learn new technologies, extract insights and value from data and how to demonstrate technology to deliver those insights through efficient data pipelines

Additionally, knowledge of cloud environments and automation/optimisation skills would be good, as well Should be experienced in ETL pipelines and aware of code standards .The candidate should be able to play a lead role towards the evolution of technology deployments across the global footprint.

Responsibilities: 

Major position responsibilities include but are not limited to the following:

• You are excited at the prospect of demonstrating technology to solve complex data problems

• Build data applications on Google cloud platform and integrate with different data sources/ tools.

• Design, develop, and maintain a world class data warehouse and analytics architecture to meet business analysis, reporting needs, and data science initiatives

• Work directly with divisional and global business users and data scientists to assist in project analysis

• Participate in the development and maintenance of ETL jobs and data pipelines to aggregate data from various on premise, cloud platforms & external data sources

• Design and develop data marts for consumption by analytics tools and end users

• Develop code standards, guidelines to manage and ensure data quality and integrity

• Optimize and scale data warehouse and data processing infrastructure

• Evaluate new technologies and constantly work towards continuous improvements in data engineering, our platform, and the organization

Required  Qualifications : 

• Bachelor’s degree required, Graduate degree or equivalent experience in Computer Science, Statistics, Informatics, Information Systems or another quantitative field would be an advantage

• Ability to work as a Data Engineer with minimum 3years of experience.

• Demonstrates expertise in data modeling, ETL development, and Data warehousing

• Knowledge of data management fundamentals and data storage principles

• Experience with Python or similar programming languages

• Working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases

• Experience in CI/CD workflow approaches

• Knowledge of Python, Terraform, docker Kubernetes, cloud functions, snowflake/BigQuery, DBT

• Experience with Git for version control

• Strong analytical, problem solving & conceptual skills

Preferred Qualifications : 

• Experience building and optimizing"big data" data pipelines, architectures and data sets.

• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and find opportunities for improvement.

• Experience with SAP data extractors, SAP Integration tools like SLT, SDI & understanding of Supply chain processes is preferred

• Experience with cloud data warehousing/Big data environments like Snowflakes, BigQuery, Google cloud storage etc is a plus

• Experience with data pipelines and streaming frameworks such as Pubsub, Spark, Airflow, Kafka etc

• Experience with RDBMS; NoSQL experience also encouraged

• Ability to embrace, learn, and apply new technologies and tools

• Familiarity with agile software development methodology

• Should be able to communicate well with both technical and non-technical teams

• Knowledge of AI tools used for data pipelines will be preferred

 

 

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