Senior Lead Software Engineer - Data Software Engineering | Workforce and Experience Technology (WXT)

JPMorgan Chase & Co.; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

JPMorgan Chase & Co. in New York seeks a Senior Lead Software Engineer to lead data engineering and drive data product offerings across HR and Employee Experience. You will guide architecture, coding, and product-minded delivery to enable scalable data platforms.

You will partner with product and architecture teams to steer SDLC, governance, and upskilling engineers while delivering TDQ/BDQ improvements and secure data pipelines in cloud environments (AWS, Databricks, GCP, Azure).

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience anticipate and solve complex technical items within your domain of expertise.
• Hands-on Data Engineering development, coding, AI-code tools and techniques, testing, automation
• Key Technical Skills: Databricks, DBX, PySpark, Spark, Terraform, Kafka, Python/Scala, Glue/EMR
• Experience with AI Developer Automation Tools and BI Consumption tools such as Sigma, Genie, Tableau
• Experience with Governance using Unity Catalogue and Data Access Governance with Immuta
• Experience in cross-functional teams of technologists
• Experience dealing with internet scale volume and size of data
• Experience in Big Data technologies handling complex data processing requirements
• Experience building data pipelines and platforms in cloud (AWS S3, Databricks, GCP, Azure)

Responsibilities

• Provide hands on delivery of data pipeline and architecture solutions that can be leveraged across multiple businesses that are easily augmented, exchanged, rotated, etc.
• Be proficient in all aspects of the data production pipeline are driven by x-as-Code (extraction, transformation, reconciliation, data quality (business, technical), security).
• Bring trends in both test-driven and data-driven development building modular designs that can be auto-repeatable as frameworks to build a data production factory, minimizing ad hoc data generation.
• Transform traditional HR/EX into modern data product offerings that scales for business needs.
• Perform as a key member of data engineering scrum teams to achieve functional technology objectives. while influencing peer leaders and senior stakeholders across the business, product, and data technology teams.
• Partner with Product and Architecture to make strategic decisions that influence teams’ resources, budget, tactical operations, and the implementation of processes and procedures.
• Be accountable for SDLC, design patterns and upskilling engineers
• Uplift and modernize data platforms driving Stability, Timeliness, Completeness, Quality (TDQ/BDQ), Security, FinOps, Operational Excellence and Ease of consumption.
• Carry governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations.
• Advance and support the firm’s culture of diversity, opportunity, inclusion, and respect

Skills

Databricks

DBX

PySpark

Spark

Terraform

Kafka

Python/Scala

Glue/EMR

AI code tools

Testing

Automation

Tools

Sigma

Genie

Tableau

Unity Catalogue

Immuta

Job description

Elevate and drive innovation, data engineering solutions, and serve as a decision maker for Firmwide HR and Employee Experience data products.

As a Senior Lead Software Engineering at JPMorgan Chase within the Employee Platforms, Workforce Experience Technology (WxT) Data and Integrations team, youlead data engineering and drive impact within teams, technologies, and data product offerings across HR, Employee Experience, CAO and EP technology. Utilize your in-depth engineering knowledge, coding and impact for data, analytics, applications, technical processes, and product management to lead multiple complex designs and initiatives making key decisions for your team, and a drive innovation and solution delivery.

Job responsibilities

• Provide hands on delivery of data pipeline and architecture solutions that can be leveraged across multiple businesses that are easily augmented, exchanged, rotated, etc.
• Be proficient in all aspects of the data production pipeline are driven by x-as-Code (extraction, transformation, reconciliation, data quality (business, technical), security).
• Bring trends in both test-driven and data-driven development building modular designs that can be auto-repeatable as frameworks to build a data production factory, minimizing ad hoc data generation.
• Transform traditional HR/EX into modern data product offerings that scales for business needs.
• Perform as a key member of data engineering scrum teams to achieve functional technology objectives. while influencing peer leaders and senior stakeholders across the business, product, and data technology teams.
• Partner with Product and Architecture to make strategic decisions that influence teams’ resources, budget, tactical operations, and the implementation of processes and procedures.
• Be accountable for SDLC, design patterns and upskilling engineers
• Uplift and modernize data platforms driving Stability, Timeliness, Completeness, Quality (TDQ/BDQ), Security, FinOps, Operational Excellence and Ease of consumption.
• Carry governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations.
• Advance and support the firm’s culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills.

• Formal training or certification on software engineering concepts and 5+ years applied experience anticipate and solve complex technical items within your domain of expertise.
• Hands-on Data Engineering development, coding, AI-code tools and techniques, testing, automation
• Key Technical Skills: Databricks, DBX, PySpark, Spark, Terraform, Kafka, Python/Scala, Glue/EMR
• Experience with AI Developer Automation Tools and the use of BI Consumption tools such as: Sigma, Genie, Tableau
• Experience with Governance using Unity Catalogue and Data Access Governance with Immuta
• Experience in working in cross-functional teams of technologists.
• Experience dealing with internet scale volume and size of data.
• Experience in Big Data technologies handling complex data processing requirements.
• Experience building data pipelines and platforms in cloud (AWS S3, Databricks, GCP, Azure)

Preferred qualifications, capabilities, and skills

• Prior Financial Services experience is preferred.