Senior Data Engineer

8x8 connects our customers and teams globally, empowering CX leaders with performance and insights to make smarter decisions, delight customers, and drive lasting business impact.

Senior Data Engineer

Engineering · Data Platform · Full-Time

As a Senior Data Engineer, you will be responsible for architecting, designing, and implementing robust data solutions to drive analytics and business intelligence initiatives. You will lead a team of data engineers to develop and maintain data pipelines, data architectures, and data management processes that ensure high quality and availability of data across the organization.

Data Pipeline Development

• Design, build, and maintain efficient and reliable ELT/ETL processes to collect, integrate, and prepare data from various sources.
• Develop scalable and high-performance data pipelines that support data ingestion, processing, and retrieval.

Data Architecture Design

• Collaborate with stakeholders and data architects to define and implement data architecture strategies and best practices.
• Evaluate and select appropriate tools and technologies to enhance data processing capabilities, including databases, data lakes, and cloud data platforms.
   

Data Quality Assurance

• Establish and enforce data quality standards, validation rules, and data governance practices to ensure data integrity and reliability.
• Monitor data pipelines for performance and accuracy, resolving issues as they arise.

Cross-Functional Collaboration

• Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions that meet their needs.
• Facilitate discussions to gather feedback on data solutions and refine processes accordingly.

Performance Optimization

• Analyze and optimize existing data pipelines and databases for performance, scalability, and cost-effectiveness.
• Develop strategies to improve data processing efficiency, including partitioning, indexing, and query tuning.

Documentation and Best Practices

• Maintain comprehensive documentation of data architectures, data flows, and standard operating procedures.
• Promote best practices in data engineering, including coding standards, version control, and testing methodologies.
• Hands-on experience with Git-based workflows, CI/CD for data pipelines, and PR-based code review practices.

Industry Trends

• Stay current with emerging technologies, trends, and best practices in data engineering and analytics.
• Continuously evaluate and recommend new tools and frameworks to enhance the data engineering capabilities of the organization.

Required

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 5+ years of experience in data engineering or related roles, with a focus on building and maintaining data pipelines.
• Proficiency in Python and experience with data processing frameworks.
• Strong knowledge of SQL and experience with relational databases (e.g., PostgreSQL, MySQL) as well as Snowflake.
• Experience with ELT/ETL tools (e.g., Matillion) extract and load patterns preferred; transformation logic managed via dbt.
• Experience with dbt (data build tool) for transformation layer development and data modeling.
• Experience with dimensional data modeling (star/snowflake schemas) and familiarity with semantic layer concepts (e.g., Snowflake Cortex Analyst, dbt metrics).
• Familiarity with data governance, data quality, and data security best practices.
• Excellent problem-solving skills, attention to detail, and a proactive approach.
• Strong communication skills with the ability to collaborate effectively with both technical and non-technical stakeholders.
• Hands-on experience with AI/LLM integration patterns with data platforms (e.g., Claude MCP, Snowflake Cortex Analyst) ability to design and support agentic data workflows.

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