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

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

Robust 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)

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📌 GCP Data Engineer (Sydney)
🏢 Tata Consultancy Services
📍 Sydney