Data Pipeline & Integration Engineer

SUMMARY: The Pipeline & Integration Engineer is responsible for developing, maintaining, and supporting enterprise ETL pipelines and data integration workflows, primarily using Informatica currently(PowerCenter / IDMC), but may require Snowflake/dbt skills in future. This role plays a key part in delivering reliable data pipelines by implementing ETL transformations, supporting production stability, and ensuring data quality, while collaborating with senior engineers and technical leads.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties and special projects may be assigned.

• ETL Development & Implementation:
• Designs, develops, and maintains ETL pipelines using Informatica and related tools.
• Builds mappings, workflows, and sessions to support data ingestion and transformation.
• Implements transformations including joins, aggregations, parameterization, and error handling.
• Ensures ETL jobs are restartable, efficient, and aligned with SLAs and dependencies.
• Minimal scripting in Python and orchestration for API integrations, event driven patterns
• Production Support & Stability:
• Monitors and supports production ETL pipelines and scheduled jobs.
• Troubleshoots ETL failures, analyze logs, and identify root causes.
• Resolves defects and data issues within defined timelines.
• Contributes to improving pipeline reliability and reducing recurring issues.
• Data Integration & Data Warehouse:
• Designs and maintains data flows across staging, ODS, and data warehouse layers.
• Develops and maintains data interfaces across systems and applications.
• Supports data acquisition strategies and integration patterns.
• Data Pipeline Optimization & Quality:
• Optimizes ETL processes for performance and scalability.
• Implements validation checks, reconciliation processes, and data quality controls.
• Ensures compliance with data governance and audit requirements.
• Collaboration & Coordination:
• Works with business analysts and stakeholders to refine data requirements.
• Coordinates with QA, scheduling, and downstream consumers for deployment and execution.
• Participates in Agile or hybrid delivery models.
• Standards, Documentation & Governance:
• Follows coding standards, naming conventions, and documentation practices.
• Participates in code reviews and design walkthroughs.
• Maintains documentation for pipelines and interfaces.
• Modern Data Platform Exposure:
• Gains exposure to cloud and modern platforms such as Snowflake, AWS, dbt, and streaming technologies.
• Supports hybrid architecture environments combining legacy ETL and modern platforms.
• Compliance & Risk:
• Support audit, reconciliation, and data lineage requirements.
• Adheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.).
• Adheres to Bank policies and procedures and completes required training.
• Identifies and reports suspicious activity.

EDUCATION

Bachelor's Degree in Computer Science, Information Systems, or related field

Experience

• 4+ years of experience in ETL / data engineering / data integrationrequired
• Hands-on experience with Informatica (PowerCenter / IDMC)required
• Strong SQL and relational database experiencerequired
• Exposure to modern data platforms tools such as Snowflake, AWS, dbt, or other cloud-based data environments, and their orchestration toolsrequired
• Familiarity with Agile or hybrid delivery modelspreferred
• Hands-on experience with Informatica ETL tools, including mappings, workflows, and sessions
• Experience supporting production data pipelines with defined SLAs and dependencies
• Exposure to modern data platforms such as Snowflake, AWS, dbt, and cloud-based data environments

Knowledge, Skills And Abilities

• Understanding of ETL/ELT and data pipeline design, required.
• Understanding of data governance, security, and regulatory requirements in banking environments, preferred.
• Understanding of data quality, reconciliation, and audit requirements, preferred.
• Strong understanding of ETL/ELT concepts, data integration, and pipeline orchestration.
• Solid knowledge of data warehouse architecture, including staging, ODS, and enterprise data warehouse layers.
• Strong SQL skills and experience querying relational databases.
• Ability to troubleshoot ETL failures, analyze logs, and identify root causes.
• Understanding of data quality, reconciliation, and audit requirements.
• Ability to follow and contribute to coding standards, documentation, and best practices.
• Strong analytical and problem-solving skills.
• Strong attention to detail and operational discipline.
• Ability to collaborate with cross-functional teams including QA, business analysts, and downstream consumers.
• Familiarity with Agile or hybrid delivery models.
• Understanding of data governance, security, and regulatory requirements in banking environments.

Additional Information

• Candidates residing in locations within BankUnited's footprint may be given preference.