Data Engineer transforming data for analysis in an insurance company. Responsible for building data infrastructures and optimizing data delivery.
About the role
- Senior Data Engineer at Clorox developing cloud-based data solutions. Leading data engineering projects and collaborating with business stakeholders to optimize data flows.
Responsibilities
- Collaborate & Lead: Work closely with business product owners, data scientists, analysts, and cross-functional stakeholders to understand the business’ data needs and provide technical solutions.
- Influence business partners to align to the technical solutions and to adhere to technical architecture standards.
- Provide technical guidance to junior engineers, BI developers, and contractors to create efficient and effective data solutions.
- Architecting and Innovate: Strong proficiency in Python, Spark, SQL, PySQL, Pandas, CI/CD methodologies is required.
- Strong data ingestion, data modeling and dimensional modeling skills using medallion lake house architecture.
- Strong BI skills to build reports & dashboards using Power BI and Tableau etc.
- Optimize and Scale: Build and maintain data pipelines to integrate data from various source systems.
- Optimize data pipelines for performance, reliability and cost-effectiveness.
- Ensure Quality and Governance: Ensure safe custody, transport and storage of data in the data platforms.
- Collaborate with Data Governance Stewards and Business Stakeholders to enforce business rules, data quality rules and data cataloging activities.
- Enhance BI Capabilities: Develop and manage business intelligence solutions for the organization to transform data into insights that can drive business value.
Requirements
- 7+ years of experience if the candidate holds BS degree in Computer Science, Information Systems or relevant streams
- 5-7 years of experience if the candidate holds MS/PhD degree
- Experience in architecting data solutions, cloud data engineering, end to end data warehouse or lake house implementations, end to end business intelligence implementations
- Minimum 7 years of experience with data engineering, data warehousing, business intelligence with substantial experience in managing large-scale data projects
- 5+ years’ experience with data solutions implementations in cloud platform technologies like Microsoft Azure, AWS etc.
- 4+ years with business intelligence using technologies like Power BI, Tableau etc.
- 4+ years of experience with Azure services like Data Factory, Databricks, and Delta Lake will be an added advantage.
- Experience in end-to-end support for data engineering solutions (Data Pipelines), including designing, developing, deploying, and supporting solutions for existing platforms
- Knowledge or experience in Microsoft D365 Dataverse and reporting in Microsoft Fabric technology
Benefits
- robust health plans
- market-leading 401(k) program with a company match
- flexible time off benefits (including half-day summer Fridays depending on location)
- inclusive fertility/adoption benefits
- more
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