Senior Engineer, Data
Hyderabad, TS, IN
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingBuild and maintain ETL/ELT pipelines on GCP services like BigQuery, Dataflow-style workflows and Cloud Composer
Build Snowflake cloud data warehouse solutions with dimensional models and secure access
Develop batch and real-time data processing pipelines
Design and execute data migrations from on-prem or legacy systems to GCP and Snowflake
Implement CI/CD pipelines for data workflows using Cloud Build or Terraform
From the employer’s posting
Build and maintain end-to-end ETL/ELT pipelines using GCP services such as: BigQuery, WorkFlow, Dataproc, Cloud Run, Cloud Functions, Pub/Sub, Cloud Composer.
Build cloud data warehouse solutions on Snowflake — dimensional models, virtual warehouses, clustering/micro-partition strategy, roles and row-level security
Develop batch and real-time data processing pipelines.
Design and execute data migration strategies from on-prem / legacy systems to GCP and Snowflake.
Implement CI/CD pipelines for data workflows using Cloud Build / Terraform.
Tools in this posting
- Python
- SQL
- BigQuery
- GCP
- Google Cloud Storage
- Kafka
- Snowflake
- Spark
- Terraform
- PySpark
- React
Source — Tool mentions in context
## Job Roles & Responsibilities * At least 5 years of experience in implementing scalable, reliable data architectures on Google Cloud Platform (GCP). * Understand data models, warehouse structures, and data lake strategies using BigQuery, Snowflake, and GCS. * Build cloud data warehouse solutions on Snowflake — dimensional models, virtual warehouses, clustering/micro-partition strategy, roles and row-level security — and integrate Snowflake within the broader GCP data ecosystem. * Follow best practices for schema design, partitioning, and clustering for performance optimization. * Very Strong Experience in Python, SQL, PySpark. * Strong hands-on expertise with Snowflake, including advanced SQL, performance and cost tuning, and secure data sharing. * Build and maintain end-to-end ETL/ELT pipelines using GCP services such as: BigQuery, WorkFlow, Dataproc, Cloud Run, Cloud Functions, Pub/Sub, Cloud Composer. * Develop batch and real-time data processing pipelines. * Implement CI/CD pipelines for data workflows using Cloud Build / Terraform. * Ensure high performance, reliability, and fault tolerance in pipelines. * Design and execute data migration strategies from on-prem / legacy systems to GCP and Snowflake. * Integrate multiple data sources (structured, semi-structured, unstructured). * Handle large-scale data ingestion using streaming and batch approaches. * Implement data validation, monitoring, and quality checks. * Ensure adherence to data governance, security, and compliance policies. * Build frameworks for data lineage and observability - Cloud Monitoring / Logging and BigQuery audit logs. * Optimize BigQuery and Snowflake queries, storage costs, and pipeline performance; tune Spark/PySpark jobs in Dataproc environments. * Implement query optimization and cost-efficient designs. * Work closely with: Data Scientists, Data Analysts, Product & Business teams. * Translate business requirements into scalable technical solutions. ## Nice To Have
## Nice To Have * Snowflake exposure or equivalent production experience across multi-cloud data platforms. * Basic working knowledge of the AI/ML tech stack (e.g., Vertex AI / ADK, model/data pipelines, embeddings, LLM integration) and how data engineering supports AI workloads. * Basic front-end exposure with Angular / React for building or supporting lightweight data applications and dashboards. * Exposure to AI/ML data pipelines (Vertex AI / ADK). * Experience with streaming frameworks (Kafka, Pub/Sub). * Strong understanding of data warehousing concepts. Job Profile(s):
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- First seen by us
- Sep 12, 2026 · 46 days ago
- Recorded sightings
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- Last seen by us
- Oct 28, 2026
- Employer says posted
- Sep 8, 2026
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Hyderabad, TS, IN
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