Data Architect

3 weeks ago

Coimbatore Tamil Nadu India, Tamil Nadu Hash Agile Technologies Full time

Key Responsibilities

  • Design and architect scalable, secure, and resilient data platforms leveraging cloud-native technologies (AWS, Snowflake, Redshift).
  • Lead the design and implementation of data pipelines (ETL/ELT) for both batch and real-time processing.
  • Build and optimize data lakes and data warehouses to support enterprise analytics and AI/ML use cases.
  • Define and implement data modeling standards, metadata management, and master data management (MDM) practices.
  • Architect event-driven and streaming solutions using Kafka, EventBridge, and similar technologies.
  • Ensure compliance with governance, data security, privacy, and regulatory requirements (HIPAA, GDPR, etc.).
  • Drive adoption of best practices in data engineering, cloud architecture, and DevOps for data platforms.
  • Collaborate with business stakeholders, data scientists, engineers, and product teams to deliver data-driven insights.
  • Provide technical leadership, mentoring, and guidance to engineering teams.

Required Skills & Experience

  • 10+ years of experience in data architecture, engineering, or related technical roles.
  • Proven expertise in the modern data stack: AWS Glue, Lambda, Kinesis, S3, Redshift/Snowflake.
  • Strong programming and scripting experience with SQL and Python.
  • Hands-on experience with workflow orchestration tools (Airflow, Prefect, Step Functions).
  • Proficiency in Big Data technologies: Spark, PySpark, Scala.
  • Solid understanding of streaming & event-driven architectures (Kafka, EventBridge/Event Bus).
  • Experience in data modeling, building data lakes/warehouses, and architecting analytical platforms.
  • Strong knowledge of data governance, security, compliance, and MDM practices.
  • Excellent problem-solving, analytical, and system design skills.
  • Exceptional communication, stakeholder management, and leadership capabilities.

Nice-to-Have Skills

  • Exposure to ML Ops and supporting AI/ML pipelines.
  • Experience with containerization and orchestration (Docker, Kubernetes).
  • Familiarity with CI/CD pipelines and Infrastructure as Code (Terraform, CloudFormation).
  • Experience in multi-cloud or hybrid-cloud environments.

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