If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place.

As a Principal Software Engineer at JPMorgan Chase within the Chief Data & Analytics Office team, you will lead a high-performing team that embeds with lines of business to deliver mission-critical, production-grade data solutions on Databricks and Snowflake. You will own outcomes end-to-end across a portfolio of forward-deployed engagements—balancing speed and innovation with enterprise-grade governance, privacy, security, resiliency, and cost discipline. You will translate firmwide priorities into executable delivery roadmaps, establish operating models that scale, and influence senior stakeholders through clear technical strategy, strong execution, and measurable business impact.

Job responsibilities

•  Own and drive a forward-deployed delivery portfolio across multiple lines of business, ensuring predictable execution, measurable outcomes, and scalable reuse of patterns on Databricks and Snowflake.

• Set the delivery strategy and operating model for Forward Deployed Engineering in Hyderabad: engagement intake, prioritization, staffing, delivery governance, and continuous improvement.

• Lead multi-functional programs that span product, platform, infrastructure, security, risk, legal, and compliance—navigating ambiguity and resolving dependencies to deliver at enterprise scale.

• Establish platform-aligned reference architectures for lakehouse/warehouse solutions, including ingestion, transformation, semantic modeling, orchestration, testing, CI/CD, observability, and data product SLAs.

• Drive privacy- and governance-by-design across all delivered solutions, partnering with stakeholders to ensure alignment with global privacy strategy and relevant firmwide initiatives (e.g., consent management, data retention, cross-border data transfer governance).

• Oversee program execution rigor: manage risks, issues, controls, milestones, budget, vendor relationships, and delivery health across the book of work.

• Develop and maintain metrics, KPIs, and dashboards that provide executive-level visibility into delivery status, platform adoption, operational health, incident trends, and compliance posture for deployed solutions.

• Prepare and deliver executive communications (including Operating Committee-level updates) on outcomes, trade-offs, progress, risks, and investment needs.

• Partner with product leadership to align forward-deployed engagements with strategic roadmaps, shaping platform capabilities and reusable accelerators based on field learnings.

• Build and lead high-performing teams: hire, coach, and retain senior engineers; set technical and execution standards; and cultivate a culture of ownership, customer focus, and engineering excellence.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 7+ years applied experience 

• Executive-level stakeholder leadership: demonstrated ability to influence and align senior leaders across business, product, and technology organizations. Experience in leading technology organizations and delivering complex, enterprise-scale programs.

• Deep expertise in Databricks and Snowflake in large enterprises, including architecture, performance tuning, cost management, security patterns, and operational excellence.

• Strong understanding of global data governance, privacy, and regulatory requirements, with the ability to translate them into pragmatic technical architecture decisions and engineering requirements.

• Proven experience with enterprise metadata, catalog, and lineage platforms, plus practical expertise with data contracts and schema governance.

• Strong knowledge of records retention, legal holds, and defensible disposal across structured and unstructured data, including backups and snapshots.

• Ability to manage multiple portfolios and competing priorities, establishing clarity, execution discipline, and transparent decision-making.

• Demonstrated proficiency evaluating and implementing technical solutions, including vendor product knowledge and vendor relationship management.

• Strong understanding of modern data platform architectures (data lakes, data warehouses, lakehouse) and distributed computing frameworks.

• Experience with enterprise-scale cloud-native data platforms, including Databricks and Snowflake, in multi-cloud and hybrid environments with complex security/compliance needs.

• Strong AWS data ecosystem familiarity (e.g., S3 patterns and common analytics services) to integrate end-to-end solutions in the firm’s environment.