Posted:1 week ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

We’re looking for a skilled and experienced Data Engineer with 5–7 years of experience, including 3–4 years leading data engineering teams on Google Cloud Platform (GCP). The ideal candidate should have worked in premium consulting environments, led cloud migration projects, and possess strong communication skills to collaborate effectively with technical and business stakeholders.This role is with our flagship product, SearchUnify, a recognized leader in AI-powered customer support and enterprise search.

Key Skills

  • 3–4 years of experience leading Data Engineering teams developing enterprise-grade pipelines on Google Cloud.
  • Hands-on expertise in GCP services like BigQuery, Dataform, and Dataplex.
  • Proven track record in migrating ETL pipelines and data warehouses to the cloud.
  • 2–3 years of recent experience with premium consulting firms.
  • Proficiency in SQL and Python scripting.
  • Experience designing secure, scalable ETL/ELT pipelines.
  • Strong understanding of data modeling and working with fact/dimension tables.
  • Knowledge of reporting tools such as Looker, Tableau, or Power BI.
  • Ability to translate GCP knowledge across AWS or Azure environments.
  • Excellent communication and stakeholder management skills.
  • Familiarity with customer support or self-service analytics.
  • Experience working with sales and marketing data domains.
  • Exposure to AI-driven platforms and large language models (LLMs).
  • Background in developing solutions for SaaS platforms.
  • Understanding of data governance and cataloging best practices.
  • Experience with cross-functional, geographically distributed teams.

Roles & Responsibilities

  • Lead the architecture, design, and implementation of cloud-native data solutions using GCP.
  • Design and deliver high-performance data pipelines for SearchUnify’s cognitive platform.
  • Own data migration projects, ensuring secure and optimized delivery.
  • Collaborate with engineering, AI/ML, and product teams to support evolving data needs.
  • Prepare high-level and low-level design documentation.
  • Review work by junior engineers and provide technical guidance.
  • Ensure project milestones are met with quality and efficiency.
  • Drive innovation and best practices in data engineering across the team.

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