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