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Data Engineering Technical Lead - VP
Location
United States
Posted
60 days ago
Salary
$125K - $150K / year
Seniority
Lead
No structured requirement data.
Job Description
Data Engineering Technical Lead - VP
Axos Bank
Role Description 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: - 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. - Apply ML for operational intelligence: Integrate predictive models to detect pipeline anomalies, data drift, and optimize compute and scheduling. - Enforce engineering excellence: Drive CI/CD, version control, peer reviews, and observability practices across the data platform. - Collaborate cross-functionally: Partner with data architects, platform engineers, analysts, and business product owners to translate business needs into technical solutions. - Mentor data engineers: Provide technical guidance, foster continuous learning, and help the team adopt modern data engineering best practices. - Optimize performance and cost: Continuously tune Spark workloads, storage tiers, and orchestration logic across Azure and GCP environments. Qualifications - 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 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 one programming language (Python, Scala, or Java). - Strong problem-solving, architectural thinking, and collaboration skills. - Excellent communicator with the ability to translate technical topics to business stakeholders. Benefits - Medical, Dental, Vision, and Life Insurance - Paid Sick Leave, 3 weeks’ Vacation, and Holidays (about 11 a year) - HSA or FSA account and 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
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