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NEXTMOVEFDE careers · United States
Axos Bank

Data Engineering Technical Lead - VP

AI summary of the role

Axos Bank seeks a hands-on VP, Data Engineering Technical Lead to modernize legacy data systems into a cloud-native Lakehouse on Azure/GCP, driving analytics, AI, and BI.

No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.

What you’ll do

  • Modernize legacy ETL pipelines: Lead the transformation of SSIS/SSRS workloads into modular, high-performance pipelines using Databricks, dbt, Fivetran, and Airflow.
  • Architect reusable data design patterns: Define and implement standardized frameworks for ingestion, transformation, curation, and consumption layers across the Lakehouse.
  • Develop and lead POCs/POVs: Experiment with new technologies (e.g., Delta Live Tables, Iceberg, streaming ingestion, AI-driven observability) to validate architecture choices and influence the enterprise roadmap.
  • Leverage AI to accelerate engineering: Use AI-enabled tools like Databricks Assistant, Cursor AI, GitHub Copilot, and dbt Mesh AI tests for code generation, automated testing, documentation, and pipeline optimization.

What you’ll bring

  • 8+ years of experience in data engineering or related technical fields, with at least 3+ years in a lead or senior role.
  • Proven experience designing and implementing data design patterns (e.g., CDC, SCD, Medallion, Data Vault, streaming, and batch patterns).
  • Deep expertise with Databricks, Apache Spark, dbt, Fivetran, Census, Airflow, and Kafka. Solid experience across Azure and/or GCP (e.g., Synapse, Data Factory, BigQuery, Pub/Sub).
  • Hands-on experience modernizing legacy ETL (SSIS/SSRS) workloads into cloud-native pipelines.

Technologies

Databricks · Apache Spark · dbt · Fivetran · Airflow · Kafka · Azure · GCP · SSIS · SSRS

About Axos Bank

Digital-first U.S. bank and financial-services platform offering consumer/business banking, lending, deposits, securities clearing, and advisory infrastructure through low-cost online channels.

Public · 1000–2000 people

Source and classification

Internal deployment & tooling · Evidence for this classification:

modernize, and scale our enterprise data platform. This role is central to our mission of transforming legacy data systems into a modern, cloud-native Lakehouse environment that powers analytics, AI, and business intelligence across the organization. As a technical lead, you will design and deliver scalable data pipelines, define data design patterns, enforce engineering standards, and leverage AI-assisted tools to accelerate modernization, improve productivity, and reduce technical debt. You will drive proofs of concept (POCs) and points of view (POVs) to evaluate emerging technologies and frameworks, ensuring that the platform remains innovative, cost-efficient, and future-ready. Responsibilities Modernize legacy ETL pipelines: Lead the transformation of SSIS/SSRS workloads into modular, high-performance pipelines using Databricks, dbt, Fivetran, and Airflow. Architect reusable
More from the job description

Axos Bank Target Range: $125,000.00 /Yr. - $150,000.00 /Yr. Actual starting pay will vary based on factors including, but not limited to, geographic location, experience, skills, specialty, and education. Eligible for an Annual Discretionary Cash Bonus Target: Eligible for an Annual Discretionary Restricted Stock Units Bonus Target: These discretionary target bonuses may be awarded semi-annually based upon your achievement of performance goals and targets. About This Job Target Range: $125,000.00 /Yr. - $150,000.00 /Yr. Actual starting pay will vary based on factors including, but not limited to, geographic location, experience, skills, specialty, and education. Eligible for an Annual Discretionary Cash Bonus Target: 10% Eligible for an Annual Discretionary Restricted Stock Units Bonus Target: 10% Axos Bank is seeking a hands-on VP, Data Engineering Technical Lead to help shape, modernize, and scale our enterprise data platform. This role is central to our mission of transforming legacy data systems into a modern, cloud-native Lakehouse environment that powers analytics, AI, and business intelligence across the organization. As a technical lead, you will design and deliver scalable data pipelines, define data design patterns, enforce engineering standards, and leverage AI-assisted tools to accelerate modernization, improve productivity, and reduce technical debt. You wi [... source excerpt omitted ...] ofs of concept (POCs) and points of view (POVs) to evaluate emerging technologies and frameworks, ensuring that the platform remains innovative, cost-efficient, and future-ready. Responsibilities Modernize legacy ETL pipelines: Lead the transformation of SSIS/SSRS workloads into modular, high-performance pipelines using Databricks, dbt, Fivetran, and Airflow. Architect reusable data design patterns: Define and implement standardized frameworks for ingestion, transformation, curation, and consumption layers across the Lakehouse. Develop and lead POCs/POVs: Experiment with new technologies (e.g., Delta Live Tables, Iceberg, streaming ingestion, AI-driven observability) to validate a [... source excerpt omitted ...] dern data engineering best practices. Optimize performance and cost: Continuously tune Spark workloads, storage tiers, and orchestration logic across Azure and GCP environments. Requirements: Bachelors degree 8+ years of experience in data engineering or related technical fields, with at least 3+ years in a lead or senior role. Proven experience designing and implementing data design patterns (e.g., CDC, SCD, Medallion, Data Vault, streaming, and batch patterns). Deep expertise with Databricks, Apache Spark, dbt, Fivetran, Census, Airflow, and Kafka. Solid experience across Azure and/or GCP (e.g., Synapse, Data Factory, BigQuery, Pub/Sub). Hands-on experience modernizing legac

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