Data Engineering Tech Lead VP

Salary: $125,000 - 150,000 per year Requirements:

• Bachelors degree
• 8+ years of experience in data engineering or a closely related technical discipline, including 3+ years in a senior or lead capacity
• Strong background in defining and implementing data design patterns such as CDC, SCD, Medallion, Data Vault, streaming, and batch approaches
• Advanced expertise with Databricks, Apache Spark, dbt, Fivetran, Census, Airflow, and Kafka, plus practical exposure to Azure and/or Google Cloud Platform services such as Synapse, Data Factory, BigQuery, and Pub/Sub
• Direct experience modernizing legacy ETL workloads built in SSIS/SSRS into cloud-native pipelines
• Demonstrated success building POCs and POVs to assess new tools, frameworks, or architectures
• Working familiarity with AI-assisted engineering tools for development, observability, or optimization
• Proficiency in SQL and at least one programming language such as Python, Scala, or Java
• Strong analytical thinking, architectural judgment, and teamwork skills
• Excellent communication skills with the ability to explain technical concepts to business stakeholders

• Lead the modernization of legacy SSIS/SSRS ETL workloads into modular, high-performance pipelines using Databricks, dbt, Fivetran, and Airflow
• Design and standardize reusable data patterns for ingestion, transformation, curation, and consumption across our Lakehouse platform
• Build and evaluate POCs and POVs for emerging technologies such as Delta Live Tables, Iceberg, streaming ingestion, and AI-driven observability
• Use AI-enabled tools such as Databricks Assistant, Cursor AI, GitHub Copilot, and dbt Mesh AI tests to speed up code generation, automated testing, documentation, and pipeline tuning
• Apply machine learning to detect pipeline anomalies, identify data drift, and improve compute and scheduling efficiency
• Promote engineering discipline through CI/CD, version control, peer review, and observability practices across the data platform
• Work closely with data architects, platform engineers, analysts, and business product owners to turn business needs into technical solutions
• Mentor data engineers by providing technical direction, encouraging continuous learning, and reinforcing modern best practices
• Improve performance and control costs by tuning Spark workloads, storage tiers, and orchestration logic across Azure and Google Cloud environments

• AI
• Airflow
• Azure
• BigQuery
• Business Intelligence
• Census
• CI/CD
• Cloud
• Copilot
• Cursor
• Data Vault
• Databricks
• ETL
• Fivetran
• GitHub
• Java
• Kafka
• Machine Learning
• Python
• SQL
• Scala
• Spark
• SSIS
• dbt
• Architect
• Security

More:

We are Axos Bank, a digital-first financial institution building modern tools and services that help individuals, small businesses, and companies manage their money how, when, and where they want. We are looking for a hands-on VP, Data Engineering Technical Lead to help us transform legacy data systems into a cloud-native Lakehouse platform that supports analytics, AI, and business intelligence across the organization. This role offers a target salary range of $125,000 to $150,000 per year, along with eligibility for annual discretionary cash and restricted stock unit bonuses, each targeted at 10%. Our employee benefits may include medical, dental, vision, and life insurance; paid sick leave, three weeks of vacation, and holidays; HSA or FSA options; a 401(k) with employer match and a 529 savings plan; and an employee mortgage loan program plus free access to an Axos Bank account with self-directed trading. We are a diverse team of dynamic, insightful, and independent innovators, and we are an equal opportunity employer committed to fair hiring and an inclusive workplace.

last updated 33 week of 2026