Cloud Data Engineer

1 day ago

Hyderabad, Telangana, India PineQ Lab Technology Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Position Summary
We are seeking a skilled
Cloud Data Engineer
to design, build, and optimize cloud-based data platforms and pipelines. The ideal candidate has deep experience with modern data architectures, distributed processing, data modeling, and cloud-native tools. This role focuses on developing scalable, secure, and reliable data solutions that empower analytics, data science, and business intelligence across the organization.

Key Responsibilities
Data Architecture & Engineering

  • Design, build, and maintain scalable ETL/ELT data pipelines using cloud-native and open-source tools.
  • Develop and optimize data lake, data warehouse, and data mesh architectures.
  • Model and structure data for analytical, operational, and machine learning use cases.
  • Implement solutions for real-time streaming, batch processing, and event-driven data flows.

Cloud Platform Engineering

  • Build and manage data infrastructure using cloud services (AWS, Azure, GCP, or multi-cloud).
  • Leverage cloud-native tools (e.g., AWS Glue/Lambda, Azure Data Factory, GCP Dataflow/Dataproc).
  • Ensure performance, scalability, and cost efficiency of data workloads.
  • Implement best practices for cloud resource provisioning, monitoring, and automation.

Data Integration & Management

  • Integrate data from various systems, APIs, SaaS platforms, and databases.
  • Manage data ingestion, transformation, validation, and lineage tracking.
  • Develop metadata-driven and reusable components for pipeline frameworks.
  • Collaborate with data governance teams to implement security, compliance, and data-quality standards.

Collaboration & Stakeholder Support

  • Work closely with analytics, BI, product, and data science teams to deliver reliable datasets.
  • Translate business requirements into technical design and data solutions.
  • Document architectural decisions, workflows, and data models.

DevOps, CI/CD & Automation

  • Implement CI/CD pipelines for data engineering workflows.
  • Manage infrastructure-as-code using Terraform, CloudFormation, ARM/Bicep, or similar tools.
  • Automate operational tasks to ensure data platform reliability and scalability.

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