Data Engineer III

Talentify; Plano (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

JPMorgan Chase in Plano, TX is seeking a Data Engineering III to design, develop, and maintain robust data pipelines and architectures. You will drive governance, performance optimization, and mentor engineers while collaborating with business, analytics and technology stakeholders.

You will stay current with AWS Data Lake, Snowflake and related technologies, translate complex requirements into scalable solutions, and ensure secure, compliant data platforms across data lake/warehouse

Qualifications

• Bachelor’s degree in CS/IT or related field.
• 3+ years in data engineering with AWS, Data Lake, and Snowflake.
• Hands-on with data lake/warehousing tech (Redshift, BigQuery, Snowflake; Spark/Flink/Trino).
• Proficient in SQL and ETL/data pipeline tools.
• Experience using enterprise AI capabilities with validation and data sensitivity awareness.
• Ability to review AI-assisted outputs before use.

Responsibilities

• Design, build, maintain and optimize scalable batch and streaming data pipelines with performance, fault tolerance and observability.
• Develop and operate workflow orchestration to schedule, monitor, and manage data movement and transformations.
• Translate business requirements into data lake/warehouse solutions meeting standards.
• Uses enterprise-authorized AI capabilities to accelerate data pipeline design and validation, handling data securely.
• Applies reuse-first, AI-assisted SDLC practices to ensure traceability and security.
• Build and maintain governance for data modeling, cataloging, ownership, and access control.
• Provide mentorship and lead technical direction through reviews and knowledge sharing.
• Stay up-to-date with AWS Data Lake, Snowflake and related technologies.
• Perform advanced quantitative analysis of large datasets to identify business trends.
• Manage data sharing and ecosystem-specific features.

Skills

AWS

Data Lake

Snowflake

Redshift

BigQuery

Spark

Flink

Trino

SQL

Kafka

Pub/Sub

AI capabilities

Education

Bachelor’s degree in Computer Science, Information Technology, or related field

Tools

Erwin

Iceberg

Hudi

Job description

Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.

As a Data Engineering III at JPMorgan Chase within the Consumer and Community Banking team, you design, develop, and maintain robust data pipelines and architectures.. You drive data governance, performance optimization, and mentor engineers while collaborating with business, analytics and technology stakeholders. You ensure scalable, secure, and efficient data solutions that support business objectives and regulatory requirements.

Job Responsibilities

• Design, build, maintain and optimize scalable batch and streaming data pipelines with strong performance, fault tolerance, and observability
• Develop and operate workflow orchestration to schedule, monitor, and manage data movement and transformations
• Translate complex business requirements into technical solutions meeting data lake and data warehousing standards.
• 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
• Build and maintain governance processes for data modeling, cataloging, ownership, and access control.
• Provide mentorship and training on data publication best practices to team members and lead the team's technical direction through standards, reviews, and knowledge sharing
• Stay up‑to‑date with advancements in AWS Data Lake, Snowflake Data Warehouse and related technologies.
• Perform advanced quantitative analysis of large datasets to identify business trends.
• Manage data sharing, exchange, and ecosystem‑specific features.

Required Qualifications, Capabilities and Skills

• Hold a Bachelor’s degree in Computer Science, Information Technology, or related field.
• 3+ years of experience in data engineering with deep AWS, Data Lake, and Snowflake expertise.
• Hands‑on experience with modern data lake and warehousing technologies (e.g., Redshift, BigQuery, Snowflake; and engines such as Spark, Flink, or Trino.)
• Apply Agile methodologies, running ceremonies and prioritizing backlogs for continuous improvement.
• Exhibit proficiency in SQL and experience with data pipeline/ETL tools.
• 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.
• Experience designing and building streaming pipelines using Kafka, Pub/Sub, or similar messaging systems
• Experience with large‑scale distributed data processing and performance tuning
• Design and implement large‑scale data solutions in cloud environments.

Preferred qualifications, capabilities, and skills

• Experience with data modeling in Erwin.
• Experience with table formats such as Iceberg, Hudi