Remote Lakehouse Ops Engineer - Iceberg DBA (Multi-Engine)

Floga Technologies; Dallas (TX); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Floga Technologies is seeking an Iceberg DBA / Lakehouse Operations Engineer to manage Apache Iceberg data layers supporting enterprise analytics. The role covers data reliability, multi-engine query performance across Spark/Spark SQL, Hive, and Impala, and modernization efforts from Hive/Teradata to Iceberg.

Remote-friendly with flexibility for Dallas, TX, based work. The candidate will oversee table maintenance, metadata management, partitioning strategies, and data modeling within a Medallion

Qualifications

• Strong hands-on experience with Apache Iceberg and/or Hive-based data lake environments.
• Strong understanding of Iceberg table architecture, metadata management, and table maintenance operations.
• Experience with table-level optimization, compaction, snapshot management, and performance tuning.
• Understanding of data modeling concepts, including normalization and 3NF.
• Knowledge of modern Lakehouse architecture and Medallion architecture (Bronze/Silver/Gold).
• Hands-on experience with Spark SQL, Hive, and Impala.
• Working knowledge of NiFi and Trino.
• Strong understanding of partitioning strategies, partition evolution, and partition pruning.
• Experience with columnar file formats such as Parquet and ORC.
• Understanding of distributed query processing and large-scale data management.
• Experience supporting multi-terabyte to petabyte-scale data platforms.

Responsibilities

• Iceberg Data Layer Ownership & Operations
• Own day-to-day operations and administration of Apache Iceberg tables supporting multiple enterprise applications.
• Ensure data reliability, consistency, and availability across Lakehouse workloads.
• Maintain operational integrity of datasets at multi-terabyte to petabyte scale.
• Monitor table health, metadata growth, and storage utilization.
• Ensure consistent data access and operational stability across environments.
• Advanced Table Management & Optimization: Minor and major compaction; Small file mitigation and optimization; Snapshot expiration and metadata compaction; Orphan file cleanup and storage management.
• Optimize data layout and query performance through file sizing, distribution, and partitioning strategies.
• Implement partition evolution and partition pruning techniques.
• Apply clustering and data ordering strategies, such as Z-ordering or equivalent approaches.
• Monitor and optimize table maintenance operations to improve query performance and storage efficiency.
• Data Modeling & Lakehouse Architecture: 3NF; Medallion architecture; align with ingestion patterns.
• Balance data integrity, normalization, and analytical query performance.
• Collaborate with data engineering teams to ensure consistent implementation of layered data architecture across applications.
• Multi-Engine Query Performance & Consistency: Spark SQL, Hive, Impala; troubleshoot bottlenecks and RCAs across engines.
• Hive & Teradata Modernization Support: migrations to Iceberg; schema alignment; data validation and reconciliation.
• Metadata & Data Lifecycle Management: manage Iceberg metadata, retention, snapshot lifecycle; governance and access controls.
• Production Support & Incident Management: support for Iceberg Lakehouse workloads; on-call readiness; RCA and corrective actions.
• Security & Data Governance: RBAC and Apache Ranger policies.

Skills

Apache Iceberg

Hive data lake

Iceberg metadata management

Table maintenance optimization

Data modeling 3NF

Lakehouse architecture

Spark SQL / Hive / Impala

NiFi

Trino

Partitioning strategies

Parquet / ORC formats

Large-scale data platforms

Tools

NiFi

Trino

Job description

Floga Technologies is seeking an Iceberg DBA / Lakehouse Operations Engineer to manage Apache Iceberg data layers supporting enterprise analytics. The role covers data reliability, multi-engine query performance across Spark/Spark SQL, Hive, and Impala, and modernization efforts from Hive/Teradata to Iceberg.

Remote-friendly with flexibility for Dallas, TX, based work. The candidate will oversee table maintenance, metadata management, partitioning strategies, and data modeling within a Medallion