Senior Data Engineer, Analytics

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senior

H1B: no

Greatminds The Senior Data Engineer owns delivery of reliable, scalable data pipelines and strengthens platform support for analytics and reporting. This role manages complex data integrations and diagnoses failures in a production environment.

Responsibilities

Lead end-to-end delivery of complex pipelines and integrations — source onboarding, secure connectivity, ingestion configuration (primarily Fivetran), validation, deployment, and operational handoff — with documentation sufficient for handoff.
Provide advanced platform support across ingestion, transformation, orchestration, monitoring, and warehouse operations, owning outcomes rather than just tickets.
Design and maintain dbt (or similar) models that transform raw data into curated, tested, documented, consumption-ready datasets.
Establish engineering standards for pipeline development — naming conventions, load strategies, data contracts, error handling, testing — to speed up time-to-production for new integrations.
Own pipeline reliability: monitoring/alerting, SLAs/SLOs for freshness and success rate, incident response, and root-cause analysis that produces preventative fixes.
Improve platform performance and cost efficiency: warehouse sizing, job scheduling, query/pipeline tuning.
Implement secure-by-design practices: least-privilege access, secure sharing, privacy/compliance support.
Partner with data governance and analytics to improve data quality and trust via validation checks, reconciliation, freshness monitoring, and source-to-target documentation.
Support deployment and change management through version control, CI/CD, and environment promotions, reducing manual effort per release.
Mentor engineers through technical guidance and code review.
Translate business needs into well-scoped technical solutions and communicate tradeoffs clearly across technical and non-technical audiences.