Collaborate with application teams, data engineers, DBAs, and platform teams to assess migration readiness and modernize legacy workloads.
Optimize data models supporting Bronze, Silver, and Gold data layers within a lakehouse architecture.
Evaluate and implement solutions for data access, query performance, and interoperability across compute engines such as Spark, Trino, Databricks, Snowflake, Teradata, or similar technologies.
Guide the conversion of ETL workloads and legacy data integration processes into modern data engineering frameworks.
Required Qualifications
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
5+ years of experience in Data Architecture, Data Engineering, or Data Platform modernization.
2+ years of hands-on experience implementing Apache Iceberg in enterprise environments.
Demonstrated experience migrating large scale datasets from traditional databases and data warehouses into object storage and lakehouse architectures.
Strong understanding of Object Storage technologies (S3-compatible platforms, Pure storage etc.).
Experience implementing and managing Iceberg catalogs
Expertise in data modeling, partitioning strategies, schema evolution, metadata management, and performance optimization.
Experience designing and implementing enterprise ETL architectures.
Strong understanding of data governance, security, lineage, and compliance requirements.
Understanding/Experience with Postgres database
Key Responsibilities
Lead the architecture, design, and implementation of enterprise data platforms utilizing Object Storage and Apache Iceberg.
Develop migration strategies and execution plans for moving data from relational databases, data warehouses, and Hadoop ecosystems into Iceberg based architectures.
Design scalable ingestion frameworks to support batch, streaming, and near real-time data loads into object storage.
Have deep understanding of Iceberg catalog structures, namespaces, partitioning strategies, schema evolution, and data lifecycle management.
Establish best practices for security, metadata management, retention, and regulatory compliance.
Collaborate with application teams, data engineers, DBAs, and platform teams to assess migration readiness and modernize legacy workloads.
Optimize data models supporting Bronze, Silver, and Gold data layers within a lakehouse architecture.
Evaluate and implement solutions for data access, query performance, and interoperability across compute engines such as Spark, Trino, Databricks, Snowflake, Teradata, or similar technologies.
Guide the conversion of ETL workloads and legacy data integration processes into modern data engineering frameworks.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
5+ years of experience in Data Architecture, Data Engineering, or Data Platform modernization.
2+ years of hands-on experience implementing Apache Iceberg in enterprise environments.
