Master Data Architect

1 day ago

Bengaluru, Karnataka, India beBeeData Full time US$ 1,50,000 - US$ 2,00,000
Senior Data Solutions Architect

We're seeking an experienced Senior Data Solutions Architect to lead the design and implementation of our data engineering solutions. In this key role, you will be a hands-on architect, building secure and scalable data platforms while mentoring our engineering teams.

As a Senior Data Solutions Architect, you will have end-to-end responsibility for designing and implementing data architectures that meet business requirements. This includes leading the implementation of data solutions on various cloud platforms (AWS, Azure, and GCP), defining and enforcing data governance, quality, and security standards.

  • Design and develop robust, scalable, and secure data architectures that meet business requirements.
  • Lead the implementation of data solutions on various cloud platforms (AWS, Azure, and GCP).
  • Define and enforce data governance, quality, and security standards.
  • Collaborate with data engineers, data scientists, and business stakeholders to understand needs and translate them into technical solutions.
  • Evaluate new technologies and tools to improve our data infrastructure and practices.

Responsibilities include creating and maintaining detailed documentation of data architecture, data flows, and processes. Additionally, you will provide technical leadership and mentorship to junior team members, staying up-to-date with the latest trends and best practices in data architecture and cloud computing.

Qualifications

To be successful as a Senior Data Solutions Architect, you should have:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Overall 8-12 years of experience with 3+ years of experience in data architecture or a similar role.
  • Proven expertise in designing and implementing data solutions on at least one major cloud platform (AWS, Azure, or GCP).
  • Solid understanding of cloud-native data services such as AWS Redshift, S3, Glue, Athena, and EMR, Azure Synapse Analytics, Data Lake, Data Factory, and Databricks, GCP BigQuery, Cloud Storage, Dataflow, and Dataproc.
  • Experience with big data technologies (e.g., Spark, Hadoop) and data warehousing concepts.
  • Strong knowledge of SQL, ETL/ELT processes, and data modeling techniques.
Preferred Skills

While not mandatory, experience with DevOps practices and tools (e.g., CI/CD pipelines, Terraform, Docker, Kubernetes) is highly desirable. Certification in one or more cloud platforms (e.g., AWS Certified Solutions Architect, Microsoft Certified: Azure Data Engineer, Google Professional Data Engineer) is also a plus.

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