VP, Data Engineering Technical Lead

Position Overview

Axos Bank is seeking a hands-on VP, Data Engineering Technical Lead to shape, modernize, and scale our enterprise data platform. You will lead efforts to transform legacy ETL systems into a modern, cloud‑native Lakehouse environment—powering analytics, AI, and business intelligence across the organization. Compensation: Target Range: $125,000.00/Yr - $150,000.00/Yr. Actual starting pay will vary based on factors such as geographic location, experience, skills, specialty, and education. You are also eligible for an Annual Discretionary Cash Bonus (Target: 10%) and Restricted Stock Units Bonus (Target: 10%), which may be awarded semi-annually based on performance.

Key Responsibilities

• Modernize legacy ETL pipelines by transforming SSIS/SSRS workloads into modular, high‑performance pipelines using Databricks, dbt, Fivetran, and Airflow.
• Architect reusable data design patterns across the Lakehouse, defining standardized frameworks for ingestion, transformation, curation, and consumption.
• Develop and lead proofs of concept (POCs) and points of view (POVs) to evaluate emerging technologies such as Delta Live Tables, Iceberg, and streaming ingestion.
• Leverage AI-assisted tools (e.g., Databricks Assistant, Cursor AI, GitHub Copilot, dbt Mesh AI tests) to accelerate engineering, automate testing, and optimize pipelines.
• Apply machine learning for operational intelligence by integrating predictive models to detect anomalies and data drift while optimizing compute and scheduling.
• Enforce engineering best practices including CI/CD, version control, peer reviews, and comprehensive observability across the data platform.
• Collaborate cross‑functionally with data architects, platform engineers, analysts, and business product owners to translate business needs into technical solutions.
• Mentor and guide data engineers, fostering continuous learning and the adoption of modern data engineering best practices.
• Optimize performance and cost by tuning Spark workloads, adjusting storage tiers, and refining orchestration logic across Azure and GCP environments.

Required Qualifications

• Bachelor’s 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 along with solid experience in Azure and/or GCP (e.g., Synapse, Data Factory, BigQuery, Pub/Sub).
• Hands-on experience in modernizing legacy ETL (SSIS/SSRS) workloads into cloud‑native pipelines.
• Demonstrated ability to build POCs and POVs that validate new tools, frameworks, or architectures.
• Working knowledge of AI-assisted engineering tools for development, observability, or optimization.
• Proficiency in SQL and at least one programming language (Python, Scala, or Java).
• Strong problem-solving, architectural thinking, communication, and collaboration skills.

Benefits & Perks

• Medical, Dental, Vision, and Life Insurance.
• Paid Sick Leave, 3 weeks’ Vacation, and approximately 11 Holidays per year.
• HSA or FSA account along with other voluntary benefits.
• 401(k) Retirement Saving Plan with Employer Match Program and 529 Savings Plan.
• Employee Mortgage Loan Program and free access to an Axos Bank Account with Self-Directed Trading.