GCP Data Engineer - ETL/ELT Pipelines & Looker Studio

• 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)