Job Description
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 infrastructureperformance,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, andbusinessstakeholdersto 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 dataengineeringtechnologies
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
Robust understanding of data lifecycle (ingestion transformation analytics)
Expertise in data modeling, data integration, andpipelineoptimization
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 Skilled 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)

📌 Gcp Data Engineer (New South Wales)
🏢 Tata Consultancy Services
📍 New South Wales