We are seeking an experienced Data Architect to help lead the design and implementation of next generation data platforms leveraging Object Storage and Apache Iceberg. This role will be responsible for architecting and executing large scale data migrations from traditional relational and analytical databases into modern lakehouse environments built on object storage and Iceberg catalogs.
The ideal candidate will have hands on experience designing enterprise data architectures, migrating data from platforms such as Hadoop, Teradata, Oracle, and other database technologies into object storage platforms. The candidate must possess deep expertise in Apache Iceberg, metadata management, data modeling, ingestion frameworks, and large-scale migration strategies.
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.
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.
Skills Required
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a 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
- Experience migrating large-scale datasets from traditional databases and data warehouses into object storage and lakehouse architectures
- Strong understanding of object storage technologies, including S3-compatible platforms and Pure Storage
- 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 or experience with Postgres databases
EXL Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EXL and has not been reviewed or approved by EXL.
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Healthcare Strength — Medical plan options include HSA, HRA, and PPO choices, with additional health-related programs such as disability coverage and an employee assistance program. Feedback suggests these options provide meaningful flexibility and coverage breadth for many roles.
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Leave & Time Off Breadth — Up to 20 days of paid time off, plus federal holidays and paid sick and safe time, are highlighted. Feedback suggests this leave structure is a notable benefit alongside core compensation.
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Retirement Support — A traditional and Roth 401(k) with up to a 3% company match and full vesting after one year is described. Feedback suggests this match and vesting timeline help bolster long-term savings.
EXL Insights
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
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