Data Architect

4 days ago

Bengaluru Dehradun Kochi, India Invok Hr Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Role & responsibilities

  • Design, build, and optimize end-to-end data pipelines and ETL/ELT workflows using Databricks, Spark, and DBT.
  • Architect and implement data lakehouse and big data solutions across cloud platforms.
  • Develop and deploy AI/ML models with strong focus on MLOps, automation, and CI/CD pipelines.
  • Implement Infrastructure as Code (IaC) using Terraform, ARM Templates, or CloudFormation for data workloads.
  • Work with Fabric, Palantir, Synapse, Snowflake, and Hadoop ecosystems for large-scale data integration.
  • Collaborate with cross-functional teams to enable data governance, lineage, and data quality frameworks.
  • Manage and optimize cloud-based data solutions on Azure, AWS, and GCP.
  • Drive DevOps best practices for continuous integration, deployment, and monitoring of data systems.

Technical Skills

Cloud Platforms: Microsoft Azure, AWS, GCP

Big Data & Data Engineering: Databricks, Spark, Hadoop, Kafka, Airflow, DBT, Palantir, Delta Lake, Azure Synapse, ADF, Fabric, Informatica, Snowflake, Talend, Glue, DataProc, NiFi

Programming Languages: Python, Scala, Java, SQL, YAML, Shell Script

AI & ML Engineering: MLOps, Generative AI, Model Deployment, Feature Engineering

DevOps & Automation: CI/CD (Azure DevOps, Jenkins, GitHub Actions), Terraform, Docker, Kubernetes

Data Architecture: Data Lakes, Data Warehouses, Lakehouse, ETL/ELT Frameworks, Metadata Management

Qualifications

  • Bachelors or Masters degree in Computer Science, Data Engineering, or related discipline
  • 8-12 years of experience in Data Engineering / AI / Cloud domains
  • Certification in Azure, AWS, or GCP Data/AI (preferred)
  • Strong problem-solving and analytical skills
  • Excellent communication and collaboration abilities

Key Highlights

  • Expertise in multi-cloud data solutions and AI-driven architectures
  • Proven track record of delivering high-performance data platforms
  • Strong exposure to MLOps, Generative AI, and cloud-native automation
  • Hands-on experience in data modernization and digital transformation projects

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