Competencies: 10+ years experience
Digital : Google Data Engineering
integrationdata engineering - 10+ years overall
Google Cloud Platform (Google Cloud Platform) - 5+ years
Job Title Integration Lead Developer (Google Cloud Platform Data Engineering)
Relevant Experience: 10+ years overall integrationdata engineering experience with 5+ years leading cloud-based integrations and data platforms on Google Cloud Platform (Google Cloud Platform).
TechnicalFunctional Skills Data Engineering & Integration
Data ingestion, transformation, orchestration, and integration patterns (batch + real-time + event-driven)
Strong understanding of ETLELT, data quality checks, schema evolution, and metadata management
API-led connectivity and microservices-based integrations
Google Cloud Platform (Google Cloud Platform)
BigQuery (BQ): data modeling, partitioningclustering, performance tuning, cost optimization, materialized views, BQ scripting
Cloud Storage (GCS): landing zones, lifecycle policies, encryption, retention
Cloud Run: containerized integration services, scaling, secure service-to-service auth
PubSub: event-driven integrations, ordering, retries, DLQ patterns, idempotency
Cloud Composer Airflow: DAG design, scheduling, sensors, backfills, SLAs, alerting
Cloud LoggingMonitoring: operational observability, dashboards, alerts
Orchestration & Pipeline Engineering
Airflow DAG development standards, reusable operatorshooks, secrets management, environment-based configurations
Dependency management, failure handling, retries, idempotent design, replay strategies
Programming Frameworks
Python (preferred) for DAGs, data processing, and integration services
SQL (advanced) for BQ transformations and optimization
Optionalplus: Java Spring Boot for microservices dbt for transformation workflows
DevOps Platform
CICD for data pipelines and services (Cloud Build Jenkins GitHub Actions)
Containerization (Docker), artifact management
IaC (Terraform preferred) for Google Cloud Platform resource provisioning
Secrets and access management (IAM, service accounts, workload identity)
Security & Governance
Data security (PIIPHI masking), encryption, least privilege IAM
Auditability, lineage awareness, and compliance-friendly design
Experience Required
Demonstrated ability to design and implement scalable integration and data platforms on Google Cloud Platform, supporting high-volume batch and real-time workloads.
Strong hands-on expertise with BigQuery, including performance tuning, cost controls, and dimensionaldata vault-style modeling as applicable.
Deep experience building and operating Airflow Cloud Composer DAGs with enterprise scheduling, SLAs, alerting, and recovery procedures.
Strong experience implementing event-driven architectures using PubSub, including replay, deduplication, and DLQ patterns.
Solid production experience with Cloud Run services for integrationmicroservice workloads and secure connectivity to internalexternal systems.
Proven ability to integrate across enterprise systems using REST APIs, file-based integrations, and messaging patterns.
Ability to produce solution designs, technical specifications, runbooks, and operational SOPs.
Roles & Responsibilities
- Lead end-to-end integration delivery for data and application integration initiatives on Google Cloud Platform (batch + streaming + event-driven).
- Architect and develop Airflow DAGs (Cloud Composer) for ingestion and transformation workflows with standardized templates, reusable components, and strong operational controls.
- Build scalable BigQuery data pipelines, optimize query performance, and implement cost governance (partitioning, clustering, query optimization, workload segregation).
- Develop and maintain Cloud Run services for integration APIs and workflow-trigger services enforce secure IAM-based access controls.
- Implement PubSub topicssubscriptions for event-based integration design for resiliency (retries, DLQ, idempotency, ordering if required).
- Establish and enforce best practices for logging, monitoring, alerting, and incident triage participate in RCA and preventive actions.
- Collaborate with architects, product owners, and downstream consumers to define interfaces, SLAs, data contracts, and operational support models.
- Support release planning, deployment, post-release monitoring, and ongoing production support for integrations and pipelines.
- Mentor engineers, conduct codedesign reviews, and ensure engineering excellence and documentation completeness.
- Drive continuous improvement through automation, standardization, and reduction of manual operational steps.
Generic Managerial Skills
Ability to lead and coordinate onsiteoffshore teams, manage deliverables, and ensure quality and timelines.
Strong stakeholder management, communication, and cross-team collaboration skills.
Self-starter with ownership mindset, strong analyticalproblem-solving capability, and ability to work with minimal supervision.
Education BSMS in Computer Science Engineering (or equivalent).
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