Data Engineer designing and building data pipelines at LexisNexis. Collaborating with partners for high - quality analytics and AI - ready data.
About the role
- Senior Data Engineer crafting and developing data products for analytical insights at Zendesk. Collaborating in an Agile environment with a focus on data warehousing and process optimization.
Responsibilities
- Collaborate with team members and business partners to collect business requirements, define successful analytics outcomes and design data models
- Serve as Data Model subject matter expert and data model spokesperson, demonstrated by the ability to address questions quickly and accurately
- Implement Enterprise Data Warehouse by transforming raw data into schemas and data models for various business domains using SQL & dbt
- Design, build, and maintain ELT pipelines in Enterprise Data Warehouse to ensure reliable business reporting using Airflow, Fivetran & dbt
- Optimize data warehousing processes by refining naming conventions, enhancing data modeling, and implementing best practices for data quality testing
- Build analytics solutions that provide practical insights into customer 360, finance, product, sales and other key business domains
- Build and Promote best engineering practices in areas of version control system, CI/CD, code review, pair programming
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery
- Work with data and analytics experts to strive for greater functionality in our data systems
Requirements
- 5+ years of data engineering experience building, working & maintaining data pipelines & ETL processes on big data environments
- 5+ years of experience in Data Modeling and Data Architecture in a production environment
- 5+ years in writing complex SQL queries
- 5+ years of experience with Cloud columnar databases (We use Snowflake)
- 2+ years of production experience working with dbt and designing and implementing Data Warehouse solutions
- Ability to work closely with data scientists, analysts, and other stakeholders to translate business requirements into technical solutions.
- Strong documentation skills for pipeline design and data flow diagrams.
- Intermediate experience with any of the programming language: Python, Go, Java, Scala, we primarily use Python
- Integration with 3rd party API SaaS applications like Salesforce, Zuora, etc
- Ensure data integrity and accuracy by conducting regular data audits, identifying and resolving data quality issues, and implementing data governance best practices.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Benefits
- Bonus
- Flexible work arrangements
- Professional development opportunities
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