Lead Data Engineer Google Cloud Platform & OCI

Job Cloud Inc.
Dallas, United States
25 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Query Performance Artificial Intelligence Data Analysis BigQuery Business Systems Cloud Computing Cloud Storage Software Quality Databases Data Discovery Information Engineering Data Governance
+22 more
Data Infrastructure Extract Transform Load (ETL) Data Mining Data Warehousing Database Testing Python (Programming Language) Oracle Databases Cloud Services Standard Sql Cloudera Software Engineering Google Cloud Sql Optimization Data Lakes Gitlab-ci Data Lineage Low Latency Google Cloud Functions Oracle Integration Oracle Cloud Infrastructure Data Pipelines Serverless Computing

Job description

We are seeking for a highly skilled and experienced Data Tech Team Lead with deep technical expertise in Google Cloud Platform, also known as Google Cloud Platform, and Oracle Cloud Infrastructure, also known as OCI. In this role, you will serve as the technical lead for a modern data platform team, helping drive the design, development, and operational support of enterprise scale data pipelines, data warehouses, and analytics environments. The ideal candidate will have a strong software engineering and data engineering background, with experience supporting complex data movement between Google Cloud Platform and OCI, optimizing analytical queries, and enabling downstream Business Intelligence, also known as BI, and Data Science use cases. Responsibilities:

  • Architect, implement, and maintain scalable data lakes, lakehouses, and data warehousing strategies across Google Cloud Platform and OCI.
  • Design resilient and low latency Extract, Transform, Load and Extract, Load, Transform pipelines to ingest, clean, and transform data from diverse transactional, operational, and business systems.
  • Lead, mentor, and support a team of data engineers, analytics engineers, and database developers.
  • Establish code quality standards and conduct architecture reviews to support reliable and scalable data solutions.
  • Partner with application, Data Science, merchandising, and supply chain technology teams to ensure the data platform delivers clean, timely, and actionable insights.
  • Support pipeline orchestration and platform operations for enterprise data environments.
  • Implement automated data testing, anomaly detection, and data lineage tracking to support trust in enterprise reporting.
  • Optimize database, warehouse, and query performance, including approaches such as BigQuery partitioning, BigQuery clustering, and OCI Autonomous Data Warehouse indexing.
  • Enforce data governance, access control policies, row and column level security, and cataloging practices to support audits and data discovery.
  • Monitor and optimize storage and compute costs associated with large scale query activity, including BigQuery slots, Serverless Dataproc, OCI Compute, and storage layers., * Google Cloud Platform
  • Oracle Cloud Infrastructure
  • BigQuery
  • Dataproc
  • Cloud Functions
  • Cloud Storage
  • Pub and Sub
  • OCI Autonomous Data Warehouse
  • OCI GoldenGate
  • Oracle Integration Cloud
  • Oracle Database Cloud Services
  • SQL
  • Python
  • GitLab CI
  • Google Cloud Platform Vertex AI
  • Data lakes
  • Lakehouses
  • Data warehouses
  • Data lineage tools and practices
  • Data quality and observability practices

Requirements

  • Eight or more years of experience in data engineering, data warehousing, or software engineering.
  • Three or more years of experience leading engineering teams.
  • Strong hands on experience with Google Cloud Platform data and analytics services, including BigQuery, Dataproc, cloud functions, cloud runners, Cloud Storage, and Pub and Sub.
  • Experience with OCI data infrastructure, including Autonomous Data Warehouse, OCI GoldenGate, Oracle Integration Cloud, and Oracle Database Cloud Services.
  • Advanced SQL and Python experience for building robust data extraction and transformation logic.
  • Experience with CI/CD pipelines, including GitLab CI.
  • Experience supporting business intelligence, analytics, or data science use cases.
  • Strong communication and collaboration skills with the ability to work across technical and business teams.

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