Lead Software Engineer, Data Engineer, Databricks

Salary: $61,000 - 101,000 per year Requirements:

• We require formal training or certification in software engineering concepts, along with 5+ years of applied experience.
• We need hands-on experience delivering system design, application development, testing, and operational stability at enterprise scale.
• We expect practical experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures with tool use, memory, and multi-step reasoning in regulated environments.
• We are looking for strong expertise in one or more programming languages, especially Python and/or Java.
• We require advanced knowledge of software application development and technical processes, with deep experience in one or more areas such as cloud, AI/ML, or data engineering.
• We value demonstrated experience leading the effective use of enterprise-authorized AI-assisted software development tools, with the ability to set team standards for validating outputs for correctness, performance, and security.
• We need a strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations, plus experience coaching senior engineers and leads on compliant usage patterns and controls.
• We require experience with large-scale data processing, microservices, API design, Kafka, Redis, Memcached, observability tools such as Dynatrace, Splunk, and Grafana, and orchestration frameworks like Airflow and Temporal.
• We expect advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance.
• We require practical cloud-native experience with AWS, Azure, or GCP.
• We need the ability to present clearly and communicate effectively with senior leaders and executives.
• Preferred experience includes modern data platforms such as Databricks or Snowflake.
• Preferred hands-on experience includes Spark/PySpark and other big data processing technologies.
• Preferred expertise includes open-source table formats and catalog services such as Apache Iceberg.
• Preferred experience includes LLM orchestration frameworks and model serving infrastructure or managed endpoints such as AWS Bedrock or Azure OpenAI.
• Preferred familiarity includes AI evaluation and observability practices such as eval frameworks, red-teaming, prompt drift detection, and cost/latency monitoring for LLM workloads.

• We develop secure, high-quality production code for data-intensive applications and platforms, while reviewing and mentoring other engineers.
• We create durable, reusable software frameworks and patterns that can be applied across teams and functions.
• We design and govern agentic AI systems, including multi-agent workflows, tool-use integrations, and human-in-the-loop controls for regulated financial services environments.
• We drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes, while setting measurable validation standards and encouraging reuse of proven patterns and automation within the SDLC/TLM toolchain.
• We apply knowledge of tools within the software development life cycle toolchain, including authorized AI-assisted development and automation capabilities, to increase the value of automation at scale.
• We establish engineering standards for large language model-based applications, including RAG pipelines, embedding workflows, vector store integrations, and model serving, with a focus on safety, observability, and reproducibility.
• We promote advanced technical methods and practices aligned with current industry standards and product development methodologies.
• We advise cross-functional teams on technology matters within our area of expertise.
• We continue to use SDLC toolchain capabilities, including enterprise-authorized AI-assisted development and automation tools, to maximize automation value at scale.

• Agentic AI
• AI
• Airflow
• API
• AWS
• Azure
• Big Data
• Cloud
• Databricks
• Dynatrace
• GCP
• Grafana
• Support
• Java
• Kafka
• LLM
• Model Serving
• NoSQL
• Python
• PySpark
• RAG
• Redis
• Security
• Snowflake
• Spark
• Splunk
• microservices
• Network

More:

We are JPMorganChase, working with hackajob to connect exceptional professionals with this opportunity in our Corporate Technology Sector. Our Lead Software Engineer role sits within an agile data engineering team focused on building and enhancing a trusted global KYC and Risk Assessment Data Platform that is secure, stable, and scalable. We are seeking a senior engineer who can lead across multiple teams, help define architecture, engineering practices, and standards, and deliver high-impact software at scale. We offer a competitive total rewards package, with base salary determined by role, experience, skill set, and location, plus potential commission-based pay or discretionary incentive compensation for eligible roles. Our benefits may include comprehensive health care, wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching. We are committed to diversity, inclusion, and equal opportunity, and our Corporate Technology team supports business functions across Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and the Corporate Administrative Office.

last updated 37 week of 2026