Senior Data Engineer

Trianz • New York City, NY

1d • Hybrid

About The Position

Trianz is seeking a Senior Data Engineer to design, build, and support data pipelines and analytics datasets that power enterprise reporting across Finance, Technology, and Operations. The role focuses on ingesting data from corporate systems, organizing it in a cloud-based data lake, and enabling reliable reporting with Amazon QuickSight. The engineer will build and maintain Python-based ETL pipelines in AWS Glue, own transformation logic, manage orchestration and metadata cataloging, and ensure data is securely processed and accessible to downstream analytics and AI tools. The position emphasizes pipeline reliability, data quality, and performance tuning; experience with dbt and Snowflake will become increasingly important as the platform evolves.

The engineer will work in a growing analytics environment to establish practical standards for data ingestion, modeling, and reporting. They will partner with stakeholders and cross-functional teams to translate business requirements into scalable data architecture and transformation logic, and support production reporting workloads and common services.

Trianz describes itself as an applied AI solutions company with more than 25 years of enterprise transformation experience, a global presence across four continents, and a portfolio of transformation solutions under the Concierto brand.

Requirements

• 14+ years of overall software development experience, with significant exposure to data-centric systems.
• 7+ years of hands-on experience in data engineering, analytics engineering, or related data platform roles.
• Strong SQL expertise and proven experience designing and building high-quality analytical datasets for reporting and business intelligence.
• Extensive experience with AWS data platforms, including Amazon S3, Amazon Athena, AWS Glue, and AWS Unified Data Catalog.
• Hands-on experience integrating data from SaaS and enterprise systems using ETL/ELT tools such as SnapLogic.
• Experience supporting and optimizing data models for BI tools such as Amazon QuickSight, Tableau, or Microsoft Power BI.
• Ability to work independently, manage priorities, and collaborate with technical teams and non-technical stakeholders.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience.
• Strong attention to detail, ability to understand the enterprise context of data, and clear communication with technical teams, business partners, and leadership.

Nice To Haves

• Experience with dbt and Snowflake as the platform evolves.
• Experience with payment systems, financial networks, and messaging protocols such as ISO 20022, SWIFT, and NACHA.
• Familiarity with financial data standards, transaction processing workflows, and reconciliation processes.
• Experience in highly regulated environments such as banking, fintech, or healthcare, with understanding of compliance requirements.
• Knowledge of advanced data security principles, including encryption in transit and at rest, tokenization, data masking, role-based access control (RBAC), and secure data governance practices.

Responsibilities

• Design, build, and maintain scalable data ingestion frameworks using AWS native services such as Glue, Lambda, S3, and Step Functions, as well as SnapLogic, to ingest data into the data lake.
• Architect and manage the enterprise data lake on Amazon S3 using Apache Iceberg, including partitioning strategies, schema evolution, metadata optimization, and lifecycle management.
• Develop robust ELT/ETL pipelines to standardize, cleanse, and enrich source-system data for analytics and operational use cases.
• Develop and maintain reporting-ready views and queries using Amazon Athena and AWS Glue metadata.
• Implement and monitor data quality frameworks, including validation rules, reconciliation checks, and anomaly detection.
• Collaborate with Finance, Technology, and Operations stakeholders to translate requirements into scalable data architecture and transformation logic.
• Establish data governance practices, including documentation, lineage tracking, access controls, and change management.
• Monitor pipeline health and data quality, investigate data issues, and support recurring reporting cycles.
• Work with Architects, Development teams, Information Security, Infrastructure, and Operations to develop requirements for common services and create and maintain functional and technical specifications and user guides.
• Help ensure Common Services operates like a product, with regular updates and a focus on the customer.
• Support the operation of the common components and services for which the team is responsible.
• Ensure adherence to change management and risk policies.
• Continue to drive modern enterprise application development with a focus on the cloud.
• Deliver tasks and projects accurately and on schedule, maintain professionalism and accountability, collaborate across functions, support strategic goals, and communicate effectively with stakeholders and external partners as needed.

Benefits

• Startup agility with enterprise impact and opportunities to experience rapid innovation cycles on Fortune 500 transformations.
• Opportunity to lead AI-driven transformation at scale.
• Opportunity to shape transformation across continents and work with diverse global teams and clients.
• Direct impact on Fortune 500 strategies and opportunities to work alongside C-suite leaders.
• Ownership, decision-making autonomy, and a zero-bureaucracy culture.

What This Job Offers

• Career Level: Senior