Senior Data Platform Specialist

20 hours ago

Chennai, Tamil Nadu, India beBeeDataEngineer Full time US$ 1,20,000 - US$ 1,70,000
Job Overview

About Us: A fast-growing consultancy creates commercial value using data & artificial intelligence for various entities.

We have a unique blend of individuals with skills across commercial consulting, data science, and software engineering. Our team is headquartered in multiple locations worldwide.

Our company was founded by two entrepreneurs in 2019. We have grown rapidly and received an investment from a financial institution. In recent times, we opened an office in the US to expand our business.

Technical Requirements:

  • Familiarity with multi-cloud data warehousing solutions (Snowflake, Redshift, Databricks, Fabric, AWS Glue, Azure Data Factory, Synapse, Matillion, DBT)
  • Proficient in SQL, Apache Spark/Python programming languages
  • Data visualization using Power BI, Tableau, or Looker
  • Full-stack technologies
  • Containerization technologies (e.g., Docker, Kubernetes)
  • CI/CD pipelines and DevOps methodologies
  • Ability to work independently, adapt to changing priorities, and learn new technologies quickly
  • Data governance frameworks and practices to ensure data integrity and regulatory compliance
  • Data quality tools and practices

Responsibilities:

  1. Design and implement data pipelines using ETL/ELT tools and techniques
  2. Configure and manage data storage solutions, including relational databases, data warehouses, and data lakes
  3. Develop and implement data quality checks and monitoring processes
  4. Automate data platform deployments and operations using scripting and DevOps tools (e.g., Git, CI/CD pipeline)
  5. Ensure compliance with data governance and security standards throughout the data platform development process
  6. Troubleshoot and resolve data platform issues promptly and effectively
  7. Collaborate with the Data Architect to understand data platform requirements and design specifications
  8. Assist with data modeling and optimization tasks
  9. Work with business stakeholders to translate their needs into technical solutions
  10. Document the data platform architecture, processes, and best practices
  11. Stay up-to-date with the latest trends and technologies in full-stack development, data engineering, and DevOps
  12. Proactively suggest improvements and innovations for the data platform

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