Specialist - Cloud Engineering

About the Role

We are seeking a Senior Data Engineer specializing in SQL and dbt to build and maintain curated analytics datasets derived from highvolume playback content platform partner and qualityofservice data

This is a handson engineering role that also requires direct stakeholder ownership The contractor will independently gather requirements clarify ambiguous requests negotiate scope and timelines communicate risks and respond to urgent stakeholder needs while maintaining data quality and engineering standards

This is not primarily a dashboarddevelopment role or a position where stakeholder communication is handled entirely by a project manager The successful candidate must be comfortable owning both the technical work and the relationship with the people requesting it

Key Responsibilities

Design build test document and maintain production dbt models

Write and optimize complex SQL over highvolume event playback subscriber content and partner datasets

Develop scalable incremental models transformations aggregations and backfill strategies

Define and maintain clear model grains metric definitions lineage dependencies and data contracts

Implement dbt tests and other validation controls to protect data quality

Investigate data discrepancies and explain findings to both technical and nontechnical stakeholders

Evaluate query performance processing cost model materialization join strategy and pipeline runtime

Troubleshoot production pipeline failures and safely coordinate fixes reruns and backfills

Own assigned work from initial stakeholder request through requirements implementation validation release and followup

Convert incomplete or ambiguous requests into clearly scoped deliverables and acceptance criteria

Triage urgent requests based on business impact technical risk and existing priorities

Communicate delivery options tradeoffs risks and realistic completion dates

Provide proactive status updates and escalate risks before they become delivery surprises

Collaborate with analytics content strategy reporting product data science and upstream dataengineering teams

Participate in code reviews and contribute to team standards reusable patterns and technical documentation

Maintain reliable workinghour overlap with USbased stakeholders and team members

Required Qualifications

Typically five or more years of experience in data engineering analytics engineering business intelligence engineering or a comparable datafocused role

Expert SQL skills including complex transformations window functions large joins dimensional modeling performance optimization and data validation

Substantial recent handson experience using dbt in a production environment

Ability to design and build dbt models from scratch rather than only executing or maintaining models created by others

Strong knowledge of dbt model organization sources references tests documentation Jinja macros incremental models dependencies and deployment practices

Experience developing efficient transformations over largevolume datasets in a cloud data warehouse or lakehouse

Experience owning production data pipelines including troubleshooting validation releases reruns and historical backfills

Strong understanding of data modeling model grain metric consistency lineage and dataquality practices

Experience using Git pull requests code review and CICDbased development processes

Professional working proficiency in spoken and written English

Availability to participate in meetings and stakeholder conversations during agreedupon US business hours

Required Stakeholder Experience

Candidates must have prior experience directly owning relationships with business product analytics reporting or other data consumers

This experience must include

Leading requirements and scoping conversations without relying on a manager or project manager as the primary intermediary

Clarifying vague requests and identifying the business decision or outcome behind them

Translating business questions into data requirements and implementation plans

Negotiating scope priority timelines and technical tradeoffs

Managing competing requests from multiple stakeholders

Responding constructively to urgent or highpressure requests

Communicating delays