GCP Data Engineer
- Design, develop, and maintain scalable ETL/ELT pipelinesusing Python, SQL, and GCP tools
- Build batch and real-time data processing workflows
- Automate data pipelines using Apache Airflow (CloudComposer) for orchestration
- Develop and manage data solutions using BigQuery, CloudStorage, Dataflow, and Pub/Sub
- Implement scalable data warehousing and lakehouse architectures
- Monitor and optimize cloud infrastructure performance,reliability, and cost
3. Data Modeling & Transformation
- Design and implement logical and physical data models
- Perform data cleansing, transformation, and aggregationfor analytics readiness
- Ensure high data quality, integrity, and consistency acrosssystems (expertia.ai)
- Enable business insights through dashboards using LookerStudio / LookML
- Collaborate with analysts and business teams to definereporting requirements
5. Collaboration & StakeholderEngagement
- Work closely with data scientists, analysts, and businessstakeholders to gather requirements
- Provide data platform support and resolve data-related issues
- Communicate technical solutions effectively to non-technicalstakeholders
6. Data Governance, Security &Compliance
- Implement data governance, access control, and security bestpractices
- Ensure compliance with data privacy regulations and enterprisepolicies
- Identify and implement performance optimizations acrosspipelines and databases
- Introduce automation and best practices for DataOps and CI/CD
- Stay updated with evolving GCP and data engineeringtechnologies
Technical Skills
- Strong programming expertise in Python and SQL
- Hands-on experience with Google Cloud Platform (BigQuery,Dataflow, Pub/Sub, Cloud Storage)
- Workflow orchestration using Apache Airflow / Cloud Composer
- Experience with ETL/ELT pipeline design and data warehousing
- Visualization and reporting using Looker Studio / LookML
Functional & Process Skills
- Strong understanding of data lifecycle (ingestion transformation analytics)
- Expertise in data modeling, data integration, and pipelineoptimization
- Familiarity with Agile / DevOps practices in dataengineering
Soft Skills
- Strong analytical and problem-solving capabilities
- Excellent communication and stakeholder management skills
- Ability to work in cross-functional, global teams
Qualifications & Experience
- Bachelor’s / Master’s degree in Computer Science, DataEngineering, or related field
- 5+ years of experience in dataengineering or similar roles
- Proven experience working with GCP-based data platforms
- Hands-on experience in Python, SQL, Airflow orchestration
Good to Have
- Experience with PySpark / Spark / Kafka (streamingpipelines)
- Knowledge of CI/CD, Docker, Kubernetes
- Exposure to AI/ML pipelines and advanced analytics
- Certifications such as Google Professional Data Engineer
- Pipeline performance and reliability (uptime, latency)
- Data quality and accuracy metrics
- Time-to-deliver data for business insights
- Cost optimization on cloud data infrastructure
- Adoption and usability of dashboards (Looker Studio)