Design, develop, and maintain
scalable ETL/ELT pipelines
using 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 aggregation
for 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
Robust 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)
#J-*****-Ljbffr

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