L2 – Senior Iceberg DBA​/Lakehouse Operations Engineer Remote

L2 – Senior Iceberg DBA / Lakehouse Operations Engineer

Location:

Remote work accepted from anywhere in US

Duration:
Long Term

Job Description:

• 4–6 years of experience in Big Data / Data Operations / DBA roles

• Minimum 1+ year of experience with Apache Iceberg or similar table formats (Hive/Delta/Hudi)

• 4+ years of experience with Cloudera ecosystem (CDP)

• Hands-on experience with:
Iceberg table operations and maintenance, Spark SQL, Hive, or Impala

• Experience in:
Production support and incident handling, Monitoring, troubleshooting, and operational support

• Apply established data modeling and Lakehouse standards in day-to-day operations

• Support:
Table structuring, Partition alignment with ingestion patterns

• Assist in maintaining consistency of datasets across Bronze/Silver/Gold layers

Required Skills:

• Strong hands-on experience with Apache Iceberg and/or Hive-based data lakes

• Understanding of data modeling concepts (normal forms) and modern Lakehouse patterns (Medallion architecture)

• Expertise in:
Table-level optimization and performance tuning, Large-scale data management (TB/PB scale)

• Experience with:
Spark SQL, Hive, Impala, NiFI, Trino

• Strong understanding of:
Partitioning strategies, File formats (Parquet/ORC), Distributed query processing

Preferred

Skills:

• Experience with:
Hive-to-Iceberg or Teradata-to-Iceberg migration, Cloudera CDP (CDE/CDW)

• Familiarity with:
Cloud platforms (AWS, Azure)

• Scripting/automation (Python, Shell)

What You’ll Work On:

• Enterprise-scale Iceberg Lakehouse platform supporting multiple applications

• Large-scale data modernization initiatives

• Performance optimization and stability of mission-critical analytical workloads

Why This Role Matters:

• Ensures data correctness and performance for downstream analytics and business-critical reporting

• Enables successful modernization from legacy platforms to Iceberg

• Maintains high availability and reliability of the enterprise data layer

Job Summary:

We are seeking a highly skilled Iceberg DBA / Lakehouse Operations Engineer to own the reliability, performance, and operational integrity of the Iceberg data layer powering enterprise analytics and business-critical applications. This role operates in a large-scale, multi-engine Lakehouse environment, supporting workloads across Spark, Hive, and Impala, and plays a key role in enterprise data modernization initiatives (Hive and Teradata → Iceberg).

The ideal candidate brings deep expertise in Iceberg table operations, metadata management, and query performance optimization, ensuring consistent, high-performance data access across platforms in a cloud-based environment. This role is critical to ensuring data accuracy and performance—any degradation directly impacts downstream reporting, analytics, and business-critical decision-making.

Key Responsibilities:

Iceberg Data Layer Ownership & Operations:

• Own day-to-day operations of Apache Iceberg tables supporting multiple enterprise applications

• Ensure data reliability, consistency, and availability across all Lakehouse workloads

• Maintain operational integrity for datasets at multi-terabyte to petabyte scale

Advanced Table Management & Optimization:

• Execute advanced Iceberg table maintenance and optimization strategies:
Compaction (minor/major) and small file mitigation, Snapshot expiration and metadata compaction to control metadata growth, Orphan file cleanup (vacuum) to maintain storage efficiency

• Optimize data layout and performance through:
File size tuning and distribution strategies, Partition evolution and pruning optimization, Clustering and ordering techniques (e.g., Z-ordering or similar patterns)

Data Modeling Standards & Lakehouse Design Alignment:

• Support and enforce data modeling best practices aligned with:
Normalized data structures (3NF) for source-aligned datasets, Medallion architecture (Bronze / Silver / Gold layers) for curated data flows

• Ensure Iceberg table design aligns with:
Data ingestion patterns (raw vs curated layers), Downstream consumption and performance requirements

• Assist in structuring datasets to balance:
Data integrity and normalization, Query performance and analytical…