Data Analytics Engineer - Senior Associate

Senior Data Analytics Engineer within JPMorganChase's Commercial and Investment Bank Finance and Business Management team builds analytics-ready data models and a trusted semantic layer to enable governance and analytics, partnering with stakeholders to translate requirements into datasets in Databricks or Snowflake.

Job details

• Location: Plano, TX (onsite)
• Salary: USD 95,000 - 150,000 per year
• Minimum experience: 3 years
• Education: Master's degree

Responsibilities

• Lead the development of analytics data models, whether dimensional or domain-focused, optimized for reporting, BI, and self-service consumption.
• Design and sustain a semantic layer with standardized metrics, dimensions, entities, and business definitions to ensure consistency across dashboards and analyses.
• Convert stakeholder requirements into clear modeling deliverables, including entities, grains, metric definitions, and acceptance criteria.
• Implement transformations primarily in SQL, with Python used for complex logic, automation, or validation as needed.
• Establish and promote data quality controls such as tests, reconciliations, and anomaly checks tied to business-critical metrics.
• Enhance model performance in Snowflake or Databricks through efficient joins and partitioning or clustering strategies, and collaborate with upstream teams to understand source systems, including NoSQL and semi-structured data, ensuring accurate business meaning.
• Set modeling standards, including naming conventions, documentation, lineage, metric governance, and change management for semantic definitions; create curated datasets and user guidance to facilitate correct use of the semantic layer.

Requirements

• 3+ years of experience as an Analytics Engineer or related role, with a Master’s degree in Information Technology, Computer Science, Management Information Systems, Operations Research, or a related field.
• Advanced SQL skills covering complex joins, performance tuning, and incremental logic.
• Strong data modeling expertise, including facts and dimensions, grains, conformed dimensions, slowly changing dimensions, and metric design.
• Proven experience building or operating a semantic layer or metrics framework, tool-agnostic, with the ability to standardize KPI logic and definitions.
• Comfort working with semi-structured data (JSON) and NoSQL sources for analytics modeling.
• Exposure to data governance concepts such as RBAC, data classification, lineage, and audit requirements.
• Hands-on experience with Snowflake and/or Databricks in an analytics context.
• Practical Python skills for data workflows, including validation, automation, and notebooks or scripts.
• Ability to partner with stakeholders, clarify ambiguous requirements, and drive toward measurable outcomes.
• Strong documentation practices and a focus on data correctness.

Technologies

• SQL
• Python
• Snowflake
• Databricks
• JSON
• NoSQL
• Tableau
• Sigma
• Looker
• Airflow
• Dagster
• Azure Data Factory

Benefits

• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching
• Commission-based pay
• Discretionary incentive compensation