Back
Medium competition: metro locations and broadly attractive senior data architect profile with some niche Lakehouse requirements.
High: Lakehouse, Iceberg, Spark, and AWS skills are domain-specific and less transferable.
High shortlisting: explicit 8+ years and mandatory deep AWS, Spark, Iceberg expertise.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead end-to-end design, architecture, and implementation of enterprise-scale AWS data platforms and Lakehouse solutions.
Provide technical leadership through solution architecture, technology selection, development, deployment, and production support.
Mentor engineering teams and collaborate with business and technical stakeholders to deliver scalable, secure, and high-performance data solutions.
8+ years of experience designing and delivering enterprise-scale Data Lake, Lakehouse, or Data Warehouse solutions on AWS.
Strong hands-on expertise in SQL, Spark/PySpark, Python, and Lakehouse architectures using Apache Iceberg.
Deep knowledge of AWS services such as EMR, S3, Athena, Glue Catalog, Aurora PostgreSQL, Lambda, and related data services.
Location: Mumbai or Bangalore; Certifications like AWS Solutions Architect Associate/Professional or AWS Data Engineer Associate preferred but not mandatory.
Experienced technical leader with proven ability to lead globally distributed engineering teams and conduct architecture/code reviews.
Strong architectural skills with capability to define cloud data platform architectures and evaluate technology trade-offs.
Deep understanding of data engineering concepts including data modeling, distributed processing, partitioning, and cloud-native batch and streaming pipelines on AWS.