Senior / Staff Data Engineer (BI) – CEG Team

Job Summary

As a Senior/Staff Data Engineer in the Customer Experience Group (CEG), you will design, build, and maintain data pipelines, models, and tools that power how CEG serves customers and agents across all contact channels. You will balance engineering work with analytics, collaborating with product, operations, and engineering teams to deliver reliable data infrastructure and insights.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and serve data from CEG systems and third-party tools.
• Develop and optimize data models including warehouse tables, marts, and views for reporting, monitoring, forecasting, and experimentation.
• Implement validation checks, anomaly detection, and monitoring for key datasets and metrics; define data definitions, SLAs, and ownership for critical tables.
• Improve performance and cost efficiency of data jobs and queries through partitioning, indexing, query tuning, and storage format optimization.
• Design and build data tools and internal products such as self-service analytics, dashboards, alerting systems, and QA tools using languages like Python, Java, Golang, or JavaScript/TypeScript.
• Partner with product and business teams to translate questions into data problems and build dashboards and reports for contact volumes, handling time, quality, and agent performance.
• Define and maintain metrics and KPIs such as CSAT, NPS, SLA, AHT, and FCR with consistent definitions across CEG teams.
• At Staff level, shape CEG’s data and tooling strategy, influence cross-team architecture, mentor junior and mid-level team members, and drive continuous improvement of team workflows.

Must haves

• 8+ years working as a Data Engineer, Analytics Engineer, or Data Analyst in a data-driven environment (Staff level typically 10+ or equivalent scope/impact).
• Strong SQL skills including complex joins, window functions, aggregation, and query optimization.
• Experience with at least one major data warehouse or big data technology such as BigQuery, Snowflake, Redshift, Hive, Spark, Vertica, or StarRocks.
• Solid experience with ETL/ELT tools or orchestration frameworks such as Airflow or dbt.
• Proficiency in at least one programming language for data and services such as Python, Java, Golang, Kotlin, or JavaScript/TypeScript.
• Experience building production-grade data pipelines and data services with attention to quality, monitoring, and maintainability.

Nice to haves

• Experience with event-driven data including logs, clickstream, customer journey, and contact flows.
• Knowledge of data modeling techniques such as dimensional modeling, Kimball, data vault, or star/snowflake schema.
• Experience with A/B testing, experimentation platforms, or causal analysis.
• Prior experience in a Staff or Tech-Lead role driving technical direction and mentoring multiple engineers or analysts.

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