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LEAD DATA ENGINEER
Kenvue
posted 3mon ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
- Provide overall leadership for data solutions in partnership with architecture and platform teams to build next generation product capabilities that drive business growth.
- Perform proof of concepts and deliver highly secure, scalable, cost-effective applications that align with the team strategy and vision.
- Stay up to date with emerging technologies, guide, and mentor other data engineers in the team.
- Focus on execution & delivery of highly reliable, high-quality data pipelines aimed at maximizing business value through data products.
- Lead data engineering teams, building and improving next generation data & analytics capabilities within DevSecOps framework.
- Work closely with the Business Analytics leaders to understand needs of the business; clearly articulating the story of value created through data & technology.
- Drive prioritization and implementation of most appropriate combination of data engineering methodologies & frameworks to ensure optimal scalability, flexibility and performance of platforms, products & solutions.
- Be an expert and a thought leader of how data and technology come together to empower the business.
- Forge trusted partnerships and be an integral part of Data Engineering, Data Architecture & Platforms and Data Science teams to adopt, scale and build data products.
- Undergraduate degree in Technology, Computer Science, applied data sciences or other related fields; advanced degree in related fields preferred.
- Demonstrated strength in examining issues, driving resolution & influencing effectively across the organization. Ability to challenge the status quo in technology & architecture.
- Superb interpersonal & communication skills (oral and written), including the ability to explain digital concepts and technologies to business leaders, as well as business concepts to technologists.
- 5+ years leading data engineering teams in Consumer/Healthcare Goods companies and excellent understanding of business domains within the industry.
- 10-12 years of progressive experience with developing full stack Data Frameworks: ETL/ELT, data analysis, compute & storage, data pipelines, orchestration.
- Minimum of 5 years hands-on experience in Cloud Architecture (Azure, GCP, AWS) & cloud-based databases (Synapse, Databricks, Snowflake, Redshift) and various data integration techniques (API, stream, file) using DBT, SQL/PySpark, Python.
- Proficient in other ETL Platforms used for data ingestion / integrations (e.g., IICS, SAP BODS, SAP Datasphere).
- 3+ years implementing data pipelines enabling data products through data mesh / fabric concepts.
- Minimum of 5 years leading data engineering teams with planning and execution using Agile methodology (Scrum/Kanban) within DevSecOps model.
- Ability to define data pipelines to address data challenges: different granularity, data gaps, sophisticated matching logic, multi-language, structured & unstructured; harmonization & normalization of data.
- Proven track record leading multiple high-profile projects with demanding deadlines, changing requirements, and working with defined resources. Ability to estimate required effort and prioritize work items appropriately.
- Thrives on a diverse company culture, celebrating the uniqueness of our employees and committed to inclusion. Proud to be an equal opportunity employer.
Employment Type: Full Time, Permanent
Functional Areas: Analytics & Business Intelligence
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