Data Engineer III at JPMorganChase · Ciudad…

Develop, test, and maintain critical data pipelines and architectures across multiple technical areas

Enigma is an analytics-focused application that transforms ServiceNow-sourced ITSM data in Snowflake into curated datasets and delivers reporting, search, and insights. We’re expanding APIs for broader firm consumption and planning a revised data architecture—while preserving the fast search experience users value today.

We’re hiring a mid-level Data Engineer to build curated analytical datasets and implement high-performance “data serving” patterns for search and APIs. This role will also contribute to evaluating architecture options (e.g., Snowflake-only vs. a dedicated serving/search layer) based on latency, cost, and operational fit.

Job Responsibilities

• Build and operate ELT pipelines into Snowflake from ServiceNow-derived sources, including incremental loads, backfills, and reprocessing.
• Develop and maintain analytics models and canonical definitions (metrics, dimensions, incident taxonomy, time-windowed aggregates).
• Design low-latency data-serving patterns for search and APIs, such as:
  • denormalized/search-optimized tables and materialized aggregates
  • precomputed facets/filters and pagination-friendly query patterns
  • strategies to minimize expensive joins at request time
• Contribute to architecture decisions for search performance:
  • define measurable non-functional requirements (e.g., p95/p99 latency targets, concurrency, freshness)
  • run/assist PoCs and benchmark approaches (warehouse-only vs. dedicated serving/search layer)
  • document tradeoffs across latency, cost, complexity, and operational risk
• Implement data quality and observability: freshness/completeness checks, schema drift detection, reconciliation, monitoring/alerting, and clear SLAs/SLOs.
• Partner with application developers to create stable, versioned data surfaces for APIs (contract-friendly schemas, safe schema evolution).
• Create and maintain runbooks and support processes; participate in incident triage where data quality or serving performance is involved.
• Build and maintain an MCP (Model Context Protocol) server—a standardized adapter that connects AI applications (e.g., LLMs/agents) to external tools, APIs, and data sources by translating AI intent into actionable system commands.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data pipeline/design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Applies reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (e.g., test generation and control validation), ensuring traceability/auditability and alignment to resiliency and security expectations.

Required qualifications, capabilities, and skills

• 3–6 years (or equivalent) experience delivering production data pipelines and curated analytical datasets.
• Strong SQL and analytics modeling skills (incremental patterns, snapshots, aggregates).
• Proficiency in Python (preferred) and/or Java for transformations, validations, and automation.
• Experience with Snowflake, including performance/cost awareness, query tuning, and secure access patterns.
• Demonstrated ability to design for performance (benchmarking, query plan reasoning, caching/materialization strategies).
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs (e.g., query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements.
• Advanced English skills

Preferred qualifications, capabilities, and skills

• Experience building integrations/servers that connect applications to tools/APIs/data sources (experience with MCP specifically is a plus).
• Experience with low-latency serving/search technologies (e.g., Elasticsearch/OpenSearch, Postgres-based serving layers, etc.).
• Familiarity with ITSM / ServiceNow datasets.
• Experience supporting data products used by multiple downstream teams (documentation, versioning, consumer enablement/change management).

About the Team

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

About the Company

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.