• Decompose complex data and business problems into specifications precise enough for AI agents to implement directly and concretely. • Design and maintain a repeatable migration pipeline that consolidates legacy mirrored Oracle schemas into a modern, single-schema PostgreSQL environment. • Implement rigorous automated reconciliation machinery (checksums, financial control totals, and row counts) to provide government acceptance evidence. • Conduct "legacy archaeology" by interrogating hundreds of thousands of lines of PL/SQL packages and triggers to extract and document load-bearing business rules. • Develop transactional schemas using Prisma and design Change Data Capture (CDC) workflows into dedicated analytics stores. • Build complete vertical slices of capability, including React-based admin UIs for data quality reports and Node.js API endpoints. • Set the technical bar for data integrity, utilizing golden-master behavioral checks to prove migrated cases still price and process identically to legacy systems. • Maintain a rigorous human-review process for all agent-generated code to ensure compliance with federal financial standards.

• Organizar, coletar e processar (ferramentas ETL) grandes volumes de dados, traduzindo os objetivos de negócios do cliente em uma estratégia de gerenciamento de informações e inteligência de negócios. • Responsável por manter os pipelines de dados e garantir a segurança no acesso as informações. • Sua atuação também pode abranger a criação e exposição de métricas (painéis) sobre os dados obtidos, garantindo assim qualidade, e integridade a estas informações.

Role Description This is a remote role that may only be hired in the following locations: NC, CA. We are seeking an experienced Lead Data Engineer to design, build, and support scalable enterprise data solutions across AWS and Snowflake platforms. The ideal candidate will have expertise in cloud data engineering, data warehousing, Snowflake, dbt, Python, and ETL/ELT technologies, with proven experience leading teams and driving data modernization initiatives. - Lead the design, development, and delivery of scalable data engineering solutions. - Build, optimize, and support data ingestion, transformation, and data warehouse pipelines using AWS, Snowflake, dbt, and Python. - Design and implement enterprise ETL/ELT frameworks, data models, data quality controls, reconciliation processes, and governance standards. - Collaborate with business and technology stakeholders to deliver trusted data products and analytics solutions. - Drive modernization of legacy data platforms and ETL workloads into cloud-native architectures. - Ensure operational excellence through performance optimization, CI/CD, testing, documentation, and production support. - Provide technical leadership, mentorship, and best-practice guidance across engineering teams. - Leverage AI-powered solutions and enterprise-approved AI tools to automate engineering tasks, improve productivity, accelerate data delivery, and reduce time-to-market. Qualifications - Bachelor's Degree and 6 years of experience in Software application development and maintenance OR High School Diploma or GED and 10 years of experience in Software application development and maintenance. - 10+ years of hands-on Data Engineering experience delivering enterprise-scale data solutions. - 5+ years of experience with AWS data services and cloud platforms, including S3, Glue, Lambda, IAM, Step Functions, and related services. - 3+ years of hands-on experience with Snowflake and dbt, including data modeling, ELT development, performance tuning, testing, deployment, and operational support. - Strong proficiency in SQL (7+ years) and Python (5+ years), with experience developing scalable data pipelines, automation frameworks, data validation processes, and performance optimization. - Hands-on experience with workflow orchestration tools such as Apache Airflow or Astronomer for scheduling, monitoring, and managing enterprise data pipelines. - Experience with enterprise ETL/ELT tools such as Informatica, DataStage, SAP BODS, SSIS, or equivalent technologies, along with strong knowledge of data warehousing, dimensional modeling, data governance, and CI/CD practices. - Practical experience using AI-powered productivity tools (e.g., GitHub Copilot, ChatGPT, Claude, Amazon Q) to improve engineering efficiency, code quality, documentation, testing, and delivery. Preferred Qualifications - Experience modernizing legacy ETL platforms such as Informatica, DataStage, SAP BODS, or SSIS into Snowflake and dbt-based cloud data architectures. - Experience with Snowflake Cortex, CDC, streaming, and real-time ingestion technologies including Kafka, Kinesis, Qlik Replicate, and Snowpipe Streaming. - Experience integrating data across AWS, on-premises, and Snowflake environments, with exposure to enterprise security, governance, and compliance frameworks. - Familiarity with Tableau or Power BI for reporting, visualization, and analytics. - Experience working within Financial Services, Banking, or other highly regulated industries with strong governance, security, compliance, audit, and change management requirements. - Relevant certifications such as SnowPro, AWS Certified Solutions Architect – Professional, AWS Certified Data Engineer, or other AWS/Snowflake cloud data platform certifications. Soft Skills - Strong communication and stakeholder management skills. - Proven leadership and mentoring capabilities. - Strong analytical, troubleshooting, and problem-solving skills. - Ability to work independently and manage multiple priorities. - Strong ownership mindset with a focus on quality and delivery. - Effective collaboration across cross-functional teams and business stakeholders. Compensation If hired in CA, the base pay for this position is generally between $129,000 and $190,000. Actual starting base pay will be determined based on skills, experience, location, and other non-discriminatory factors permitted by law. For some roles, total compensation may also include variable incentives, bonuses, benefits, and/or other awards as outlined in the offer of employment. Benefits Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits .

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director, Data Engineering Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview The Mastercard Services Technology team is looking for Director of Data Engineering, to drive our mission to unlock potential of data assets by consistently innovating, eliminating friction in how we manage big data assets, store those assets, accessibility of data and, enforce standards and principles in the Big Data space both on public cloud and on-premise set up. This is a high-impact role where the person will be responsible for driving the design and implementation of modern, scalable, and secure data platforms across AWS and Azure. The scope of the role includes establishing platform strategy, enforcing governance, defining and propagating best practices across Data Platforms. The role will also involve collaborating with cross-geography teams of data engineers and platform engineers. We're not just looking for an architect-we want a builder, mentor, and leader who thrives in fast-paced environments and takes pride in delivering real, measurable value. If you enjoy rolling up your sleeves while shaping long-term strategy, this role is for you. Role • Design and architect end-to-end cloud-native solutions with a focus on modern data platforms, including Lakehouse architectures leveraging S3, Azure Data Lake, Databricks, and related tools. • Provide technology leadership and people leadership to a team of global engineers. • Lead by doing - drive DevOps initiatives including CI/CD pipeline creation, infrastructure-as-code implementation, and automated environment provisioning across multi-cloud environments. • Set and enforce cloud security best practices, including IAM, encryption, network security, and regulatory compliance (e.g., GDPR, HIPAA). • Establish and enforce enterprise-grade data governance frameworks, including data cataloging, lineage, classification, and access control, leveraging tools like Lake Formation or Azure Purview. • Design and lead implementation of robust data engineering pipelines, including ETL/ELT, data lakes, and data warehouses. • Implement Lakehouse architectures using the medallion model (Bronze, Silver, Gold) with deep integration into AWS services (Glue, Lake Formation) and analytics engines (Databricks, EMR, Athena). • Translate business requirements into scalable technical solutions, working closely with product, engineering, and data stakeholders. • Mentor and guide engineers and DevOps teams, fostering a culture of technical excellence, ownership, and continuous improvement. • Continuously monitor, troubleshoot, and optimize infrastructure and data workflows for performance, reliability, scalability, and cost efficiency. • Document architecture decisions and operational standards and help establish technical best practices across teams. • Stay ahead of emerging technologies and trends in cloud, data, and DevOps to keep our platform future ready. • Participate in architectural discussions , iteration planning, and feature sizing meetings • Adhere to Agile processes and participate actively in agile ceremonies • Stakeholder management skills All About You • Bachelor's degree in computer science, Engineering, or related field (or equivalent experience). • 15+ years of experience in cloud and data platform architecture, DevOps, or related technical roles. • Proven hands-on expertise with AWS and Azure services including S3, EC2, Lambda, Glue, Redshift, Lake Formation, Azure Data Factory, Fabric, Synapse, and Databricks. • Strong track record of building DevOps pipelines and infrastructure-as-code using Terraform, CloudFormation, ARM templates, Azure DevOps, or GitLab CI/CD. • Solid understanding of cloud security concepts, IAM design, data encryption, and governance frameworks. • Experience with data engineering frameworks such as Spark, PySpark, and large-scale ETL systems. • Proficiency in scripting and automation using Python, Bash, or PowerShell. • Demonstrated success in architecting and delivering medallion architecture solutions in a production environment. • Excellent problem-solving, decision-making, and communication skills. • Proven leadership experience, with the ability to guide cross-functional teams, influence stakeholders, and drive outcomes. • Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, ECS, AKS). • Familiarity with data governance tools such as AWS Lake Formation or Azure Purview. • Knowledge of observability and logging stacks (e.g., CloudWatch, Azure Monitor, ELK). • Experience with cloud cost optimization strategies and financial management. • Exposure to MLOps workflows and integration with machine learning pipelines. • Comfortable working in Agile/Scrum development environments. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.