• Build and operate ingestion, ELT/ETL, and orchestration pipelines that move data from our MongoDB Atlas operational store and other sources into our analytical and AI-serving layers • Implement layered (medallion-style) transformations with idempotent, backfillable, incrementally loaded jobs • Apply deduplication, normalization, and validation so downstream data is high-quality and trustworthy • Modernize legacy / homegrown data flows via incremental, strangler-fig migrations that keep production stable • Build embeddings and vector pipelines, and the feature/retrieval-ready datasets that RAG, semantic search, and agentic workloads depend on • Make production data AI-ready in practice: well-structured, lineage-tracked, and retrieval-friendly, in partnership with ML and application engineering • Implement real-time and change-data-capture flows from MongoDB (Change Streams / CDC) where workloads require fresh data • Implement the canonical data model, schemas, and data contracts defined by the Data Architect — enforced in-repo so other teams build against stable definitions • Exercise sound persistence judgment in execution: land data in the right store (document / NoSQL, vector, analytical) per the architectural direction • Contribute to build-vs-buy decisions by prototyping with proven, industry-standard tooling over custom development • Establish testing, data-quality, and lineage checks for the pipelines you own, with clear alerting and runbooks • Instrument pipeline observability (freshness, volume, schema-drift, cost) so failures are caught before consumers feel them • Use AI-assisted development tools (Claude Code, Copilot, Cursor) as a force multiplier for transformation logic, query tuning, and migration scripting • Partner with database engineering on extracting from and protecting the production store • Partner with the Data Architect on implementing target-state patterns and surfacing what's hard to build • Partner with ML, AI, and application engineers on the data they consume — shaping and governing it so it's safe and ready to build on

• Join a motivated, career-oriented team as a Data Engineer. • Design, build, and maintain ETL pipelines across diverse data sources. • Implement data management standards and ensure data quality practices. • Collaborate with teams to optimize data loading and management processes.

Title: Data Engineer Locations: Los Angeles; New York; Remote; San Francisco Hybrid Job Description: Who We Are EDO is the TV outcomes company. Our leading measurement platform connects convergent TV airings to the ad-driven consumer behaviors most predictive of future sales. EDO empowers the advertising industry to maximize media impact, optimize creative performance, and know the fair value of every impression - across linear and streaming for an increasingly programmatic world. By combining immediate engagement signals with world-class decision science and vertical AI, EDO equips industry leaders with syndicated, investment-grade data that aligns media to business results - with detailed competitive, category, and historical insights. Leading brands, agencies, networks, streamers, and studios trust EDO's TV intelligence to know what works. EDO is headquartered in New York City and Los Angeles with an office space in San Francisco. We recognize the benefits of hybrid working, and want to create the best balance to ensure we can continue working together effectively. For those who reside full-time in NYC, SF, or LA: we have a hybrid work policy of three days in the office and two remote work days. The Role As a Data Engineer at EDO, you will join a team of talented engineers working closely with Data Scientists to build and scale our next-generation Ad EnGage data pipeline. This pipeline measures and optimizes the effectiveness of advertising by combining and analyzing a wide range of datasets, including advertising occurrence data, outcome data, identity resolution data, and more. Our clients rely on these insights to make critical decisions about their advertising strategy. You will work with large-scale datasets (hundreds of TBs to petabyte-scale systems) using a modern data stack centered on AWS, Airflow, dbt, and Snowflake. You'll contribute to building reliable, high-quality data pipelines and improving the performance, scalability, and observability of our data platform. What We Are Looking For - 3-6 years of experience as a Data Engineer. - Hands-on experience with cloud data platforms (Snowflake or Redshift preferred). - Strong understanding of data warehousing concepts and cloud infrastructure (AWS preferred). - Experience building and maintaining ETL/ELT pipelines using tools such as Airflow and dbt. - Strong SQL skills, including query optimization, data modeling, and working with large datasets. - Proficiency in at least one scripting language, preferably Python. - Hands-on experience with large-scale, complex data pipelines operating at billions to trillions of rows of data. - Ability to work independently on well-scoped projects, collaborate with cross-functional partners, and deliver production-ready solutions. Compensation and Benefits EDO offers a competitive compensation package. Components of compensation include: - Mid-stage equity and competitive salary - Flexible Time Off - Medical, dental and vision coverage: EDO provides full coverage for individual medical plans and partial coverage for dependent or family plans. - 401(k) plan, FSA, HSA - Commuter Benefits - When in an office, employee meals, snacks, and more In compliance with New York and California Pay Transparency Law, the salary range for this position is $120,000 to $160,000 plus equity. We note the salary information as a general guideline only, as actual compensation may vary from posting. We will consider various factors to determine the offer for this role, including the scope and responsibilities of the position, relevant work experience, key skills, training, and business considerations.

Title: Enterprise Storage Engineer Job Description: Job Level: Vice President Location: Charlotte, NC, US, 28202 Employment Type: Full Time Requisition ID: 7596 SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG’s shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges. In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization’s extensive global network. The Group’s operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC MANUBANK, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd. Role Description JRI-America, the technology subsidiary of Sumitomo Mitsui Banking Corporation (SMBC), requires a Storage Technologies Administrator to assist in the management on premises and cloud data storage. You will be part of a cross-functional team based in North America (NYC, NJ) supporting global application implementation, maintenance, and troubleshooting. The role requires some off-shift evening and weekend work as part of an on-call and skill-based rotation within a hybrid on-site and remote workplace design. Emergency response may occur beyond assigned hours. Role Objectives • Installation, configuration, maintenance, and troubleshooting of infrastructure supporting on-premises and cloud-based applications, focused on data storage related components. • Working with other system administrators to support the entire storage I/O stack across platforms, applications, and levels of virtualization. • Capacity Planning and Performance Analysis • KTLO and project tasks for installations and upgrades • Data protection, risk mitigation and design of self-service tasks • Consolidated Reporting & Analytics • Process Automation wherever possible. • Other tasks as assigned Qualifications and Skills • Experience with any of the elements in our technology portfolio below • A desire to refine and enhance your present skills • Ability to identify, manage and mitigate risk • Ability to overcome technical challenges on your own or with vendor assistance • Good communication skills both verbal and written • Proactive and capable of owning an issue to completion • Ability to manage your own time with minimal oversight Our technology mix includes • Cloud Computing (Azure, AWS) • Storage Platforms (VMAX, PowerMax, Unity PowerStore, Isilon/PowerScale, ECS, VPLEX, NetApp, IBM COS, Storworks, Spectralogic, Data Domain, Azure, S3) • Container (Kubernetes, Openshift ) • Operating systems (Windows, Red Hat Linux, AIX, HP-UX, VMware) • Ransomware prevention and remediation (Rubrik Security Cloud) • Process Automation (Ansible, Python, Rest API, JSON, Dell Appsync, ServiceNow, shell scripts, Terraform, VMware vRealize, Solutions Enabler) • Data Protection including snapshots, replication, and backups (Rubrik, TSM) • Full stack performance analysis (LogicMonitor, Virtual Wisdom, EG) • Replication (SRDF, SnapMirror, SyncIQ) • Reporting, Capacity management and forecasting (VIPR SRM, PowerBI, Arxview) • Monitoring (Virtual Wisdom, Vipr SRM, ServiceNow, Tivoli, Dell CloudIQ, NetApp ActiveIQ, Solutions Enabler) • Storage Area Networks (Cisco MDS, DCNM, Powerpath) • SAN and NAS storage protocols (Fiber Channel, CIFS, NFS) • Virtualization and Converged Infrastructure (VXBlock, VxRail, IBM PowerVM, Cisco UCS, PowerFlex) • Report Design and Generation (PowerBI, Virtual Wisdom) • Help Desk response (ServiceNow) • Project Management (Microsoft Project) • Database (Oracle, SQL) • Security Toolsets • Task and Knowledge Management (SharePoint, ServiceNow, Confluence, JIRA) • Machine learning • Technology Recovery and Resiliency, Workload Mobility Additional Requirements SMBC’s employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA-registered roles for which in-office attendance for the entire workweek is required. SMBC provides reasonable accommodations during candidacy for applicants with disabilities consistent with applicable federal, state, and local law. If you need a reasonable accommodation during the application process.