Consultant - Data Engineering

LatentView

$120K — $150K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7-10 years of experience in Data Engineering with a leadership track record
  • Demonstrated success in architecting end-to-end data solutions
  • Expertise in the Google Cloud Platform ecosystem
  • Hands-on experience with BigQuery, GCS, Dataproc, and Dataflow
  • Experience in managing complex financial datasets and building data pipelines
  • Background in delivering self-service analytics and AI-ready infrastructure

Responsibilities

  • Spearhead the design and implementation of the GCP Data Mesh
  • Architect core components of a standardized Data Platform for global business units
  • Lead the design of the Gold layer for optimized BI dashboards
  • Oversee the integration of enterprise domain systems with resilient data pipelines
  • Build the enterprise Semantic Layer to support self-service analytics
  • Embed automated data quality checks and observability dashboards
  • Drive advanced BigQuery optimization strategies for high-volume data

Benefits

  • Collaborative work environment with strategic cross-functional teams
  • Opportunity to work on cutting-edge data engineering technologies
  • Focus on innovation and best practices in data architecture
  • Access to ongoing professional development and training opportunities
  • Culture prioritizing data quality and governance practices
Full Job Description
Designation: Consulatant - Data Engineering

Level: L3

Experience: 7 to 10 years

Location: San Jose, California, United States

Job Description

Key Responsibilities

Architectural Leadership & Delivery

Data Mesh Orchestration: Spearhead the design and implementation of the GCP Data Mesh, championing domain-oriented ownership and decentralized governance.

Platform as a Service: Architect core components of a standardized Data Platform, providing scalable and reusable capabilities across diverse global business units.

Medallion Architecture Mastery: Lead the design of the Gold layer (Fact & Dimension tables), ensuring datasets are highly optimized for executive BI dashboards and downstream consumption.

Pipeline Engineering: Oversee the integration of enterprise domain systems by designing resilient, incremental data pipelines that handle complex financial datasets with high fidelity.

Semantic Layer & Data Products: Build the enterprise Semantic Layer to serve domain-specific Data Products, enabling self-service analytics and an AI-ready data infrastructure.

Governance & Optimization

Observability & Quality: Embed automated data quality checks and comprehensive observability dashboards directly into the platform to ensure "trust by design."

Performance Tuning: Drive advanced BigQuery optimization strategies, including clustering, partitioning, and indexing, to manage high-volume data warehouse performance.

Strategic Collaboration: Act as the lead architectural partner for Domain SMEs, ensuring platform reliability while maintaining alignment with Agile delivery milestones.

Technical Qualifications

Experience Profile

Industry Tenure: 10-12 years in Data Engineering, with at least 3-5 years in a lead or managerial capacity.

Proven Track Record: Demonstrable success in architecting end-to-end business solutions from discovery to production.

Cloud Expertise: Deep, hands-on mastery of the Google Cloud Platform (GCP) ecosystem, including:

Storage/Compute: BigQuery, GCS, Dataproc, Dataflow.

Orchestration & Messaging: Cloud Composer (Airflow), Pub/Sub, Cloud Functions.

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