About the role
- We are seeking a highly accomplished and visionary Advanced Data Engineer / Technical Anchor to join our team.
- In this role, you will serve as the technical lead and architectural authority, designing enterprise-grade Cloud Data Solution Architectures leveraging Python, Cloud Dataproc (Spark), BigQuery, Astro (Airflow), and Terraform.
- You will act as a strategic partner between engineering teams and business leadership, establishing organizational CI/CD standards (Tekton, GitHub) and security scanning controls (Checkmarx, FOSSA, SonarQube).
- You will govern Cloud Run audit signals and GCS log archival frameworks, and mentor engineering talent to maximize the long-term strategic value of our data platform.
- Google Cloud Platform (Biq Query, Dataproc, TERRAFORM, Tekton, Cloud Run, AIRFLOW, POSTGRES, Python)
- Security scanning controls (Checkmarx, FOSSA, SonarQube)
- Engineer II Exp: 4+ years Data Engineering work experience
- Expert mastery of Python, distributed computing with Spark on Cloud Dataproc, and advanced BigQuery data modeling, query optimization, and cost management.
- Bachelor's Degree
- Technical Anchor & Solution Architecture: Act as the lead engineer and domain expert, designing enterprise-grade Cloud Data Solution Architectures, implementing advanced design patterns, and guiding technology selection across the platform.
- Strategic Roadmap Alignment: Partner with business and engineering leaders to align technical roadmaps with organizational goals.
- Provide strategic advice on "build vs. buy" decisions to maximize long-term business value.
- IaC & CI/CD Strategy: Establish organizational standards for Infrastructure as Code using Terraform.
- Standardize automated release pipelines via GitHub and Tekton, embedding mandatory quality, security, and license compliance controls (Checkmarx, FOSSA, SonarQube).
- High-Performance Distributed Processing: Architect and optimize large-scale real-time and batch data processing systems leveraging BigQuery, Dataflow, Dataproc, Cloud Run, Pub/Sub, and distributed computing frameworks on GCP.
- Platform Health & Quality Metrics: Establish organizational coding patterns, reusable frameworks, and SLO compliance.
- Introduce and drive Software Engineering (SWE) metrics, including DORA metrics (lead time, deployment frequency, MTTR, change-failure rate), code coverage, cyclomatic complexity targets, and P99 latency standards.
- Data Governance & Enterprise Security: Drive the strategy and implementation for enterprise data governance, metadata management, data lineage, and strict GCP security controls (IAM, VPC Service Controls, encryption).
- Resilience, Observability & Incident Leadership: Establish deployment and observability standards; lead critical incident resolution and Root Cause Analysis (RCA) to implement permanent solutions and address technical debt.
- Mentorship & Culture: Mentor engineers across teams, conduct high-impact code reviews (Code Guardians), drive cultural change, and represent organizational technical excellence internally and externally (tech talks, blogs, open-source).