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.\n

ESSENTIAL DUTIES AND RESPONSIBILITIES

include the following. Other duties and special projects may be assigned.

ETL Development & Implementation:

\nDesigns, develops, and maintains ETL pipelines using Informatica and related tools.\nBuilds mappings, workflows, and sessions to support data ingestion and transformation.\nImplements transformations including joins, aggregations, parameterization, and error handling.\nEnsures ETL jobs are restartable, efficient, and aligned with SLAs and dependencies.\nMinimal scripting in Python and orchestration for API integrations, event driven patterns\n

Production Support & Stability:

\nMonitors and supports production ETL pipelines and scheduled jobs.\nTroubleshoots ETL failures, analyze logs, and identify root causes.\nResolves defects and data issues within defined timelines.\nContributes to improving pipeline reliability and reducing recurring issues.\n

Data Integration & Data Warehouse:

\nDesigns and maintains data flows across staging, ODS, and data warehouse layers.\nDevelops and maintains data interfaces across systems and applications.\nSupports data acquisition strategies and integration patterns.\n

Data Pipeline Optimization & Quality:

\nOptimizes ETL processes for performance and scalability.\nImplements validation checks, reconciliation processes, and data quality controls.\nEnsures compliance with data governance and audit requirements.\n

Collaboration & Coordination:

\nWorks with business analysts and stakeholders to refine data requirements.\nCoordinates with QA, scheduling, and downstream consumers for deployment and execution.\nParticipates in Agile or hybrid delivery models.\n

Standards, Documentation & Governance:

\nFollows coding standards, naming conventions, and documentation practices.\nParticipates in code reviews and design walkthroughs.\nMaintains documentation for pipelines and interfaces.\n

Modern Data Platform Exposure:

\nGains exposure to cloud and modern platforms such as Snowflake, AWS, dbt, and streaming technologies.\nSupports hybrid architecture environments combining legacy ETL and modern platforms.\n

Compliance & Risk:

\nSupport audit, reconciliation, and data lineage requirements.\nAdheres 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.).\nAdheres to Bank policies and procedures and completes required training.\nIdentifies and reports suspicious activity.

EDUCATION

\nBachelor's Degree in Computer Science, Information Systems, or related field\n

EXPERIENCE

4+ years of experience in ETL / data engineering / data integrationrequired\nHands-on experience with Informatica (PowerCenter / IDMC)required\nStrong SQL and relational database experiencerequired\nExposure to modern data platforms tools such as Snowflake, AWS, dbt, or other cloud-based data environments, and their orchestration toolsrequired\nFamiliarity with Agile or hybrid delivery modelspreferred\nHands-on experience with Informatica ETL tools, including mappings, workflows, and sessions\nExperience supporting production data pipelines with defined SLAs and dependencies\nExposure 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.\nUnderstanding of data governance, security, and regulatory requirements in banking environments, preferred.\nUnderstanding of data quality, reconciliation, and audit requirements, preferred.\nStrong understanding of ETL/ELT concepts, data integration, and pipeline orchestration.\nSolid knowledge of data warehouse architecture, including staging, ODS, and enterprise data warehouse layers.\nStrong SQL skills and experience querying relational databases.\nAbility to troubleshoot ETL failures, analyze logs, and identify root causes.\nUnderstanding of data quality, reconciliation, and audit requirements.\nAbility to follow and contribute to coding standards, documentation, and best practices.\nStrong analytical and problem-solving skills.\nStrong attention to detail and operational discipline.\nAbility to collaborate with cross-functional teams including QA, business analysts, and downstream consumers.\nFamiliarity with Agile or hybrid delivery models.\nUnderstanding of data governance, security, and regulatory requirements in banking environments.

ADDITIONAL INFORMATION

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