Develop and maintain efficient data models and pipelines, oversee data quality and governance efforts, and collaborate with cross-functional teams to deliver scalable data solutions that support strategic decision-making and analytics.

• Capture & Ingestion. Own the full capture path from wire to lake: decode and normalize raw exchange feeds (pcap, multicast UDP / ITCH / FIX) and vendor sources (OneTick, Refinitiv, Bloomberg, ICE) into a unified canonical model with nanosecond timestamps. Build batch + stream pipelines (Airflow, Spark, dbt) for tick and reference data. Own L2/L3 order-book reconstruction with gap handling. Provide Python and Rust producer SDKs for internal feed handlers. • Storage & Modeling — Apache Iceberg. Own the Iceberg-over-S3 lakehouse: design partitioning, sort orders, and row-group layout for fast scans; manage schema evolution, snapshots, time travel, compaction, and TTL. Maintain reference data as slowly-changing tables with point-in-time correctness for backtests. Drive storage cost optimisation via compaction, tiering, and snapshot expiry. • Tooling & Libraries. Build libraries for schema management, data contracts, validation, and lineage on top of the Iceberg catalog. Develop shared access services (Spark + Polars) so Research, backtesting, and trading share one normalized data layer, including gap detection and pcap-vs-lake reconciliation. • Reliability & Observability. Embed monitoring, alerting, SLAs/SLOs, and CI/CD across capture and pipeline layers on Kubernetes (EKS). Own data-quality dashboards and incident runbooks for the capture fleet. • Collaboration. Partner with Quant Research, Data Science, Backend, and DevOps to translate requirements into platform capabilities and champion market-data engineering best practices.

Title: Marketing Data and Analytics Engineer Location: New York, NY, USA Job Description: Full time job requisition id JR100045 About the Role Fortune Media is building a modern, data-driven marketing technology practice from the ground up. This is an early and foundational hire on a new martech team — a rare opportunity to define how data flows, behaves, and is governed across our customer-facing systems. You'll sit at the intersection of data engineering and marketing operations: designing the pipelines, definitions, and governance structures that connect Salesforce Sales Cloud and Marketing Cloud today, and that will scale into a broader CDP and ESP ecosystem over the next 12–24 months. You won't just maintain the systems — you'll help architect what they become. This role reports to the Director of Martech & CRM and works closely with marketing, technology, editorial, events, and revenue operations stakeholders. What You'll Own Data Architecture & Flows - Design, build, and maintain data pipelines between Salesforce Sales Cloud, Marketing Cloud and any future ESPs, and adjacent systems (event platforms, subscription tools, analytics layers) - Ensure reliable and performant data syncs within the integration architecture between Sales Cloud and Marketing Cloud Connect and any future ESP and tools - Evaluate and help implement future ESP and CDP tooling, defining how data enters, moves through, and exits each system - Document all data flows, field mappings, and transformation logic in a centralized, accessible way Data Governance & Definitions - Establish and maintain a data dictionary: canonical definitions for contacts, leads, accounts, subscribers, and audience segments across systems - Enforce data quality standards — deduplication rules, field validation, consent flags, suppression logic — with an eye toward a unified customer "golden record" - Partner with the Salesforce Developer to ensure custom objects, fields, and automations conform to governance standards - Champion compliance hygiene: CAN-SPAM, GDPR, and opt-in/opt-out data integrity across all marketing sends Analytics & Measurement - Build and maintain reporting frameworks for email performance, audience health, list growth, and data quality metrics - Surface actionable insights to marketing and revenue stakeholders — deliverability trends, segment performance, data decay, contact coverage gaps - Support attribution modeling and funnel reporting as Sales Cloud and Marketing Cloud mature Stakeholder Partnership - Serve as the internal expert and translator between marketing operations, engineering, and business stakeholders on data questions - Work with the Marketing Cloud Solutions Architect on technical implementation decisions - Contribute to vendor evaluation and RFP processes as the team considers CDP and ESP investments What You Bring Required - Demonstrated ability to solve complex, high-scale engineering problems through clean, efficient code. Strong proficiency in at least one major programming language (e.g., Python, Go, Java) beyond basic scripting for data manipulation. - System Design & Distributed Architecture: - Expertise in designing scalable, fault-tolerant distributed systems. - Deep understanding of system design trade-offs (e.g., CAP theorem, latency vs. throughput, synchronous vs. asynchronous processing) in the context of enterprise data pipelines. - Advanced Data Modeling: Beyond SQL proficiency, candidates should have a deep understanding of NoSQL vs. Relational schemas and how to optimize data structures for high-performance retrieval in a CDP/CRM environment. - 2–6 years of experience in a data, data engineering, marketing operations, or martech-focused role - Hands-on experience with Salesforce Sales Cloud and Marketing Cloud — you understand how the two systems connect and where they break - Fluency in SQL; ability to query, transform, and validate data independently - Working knowledge of data governance concepts: data dictionaries, lineage, deduplication, and master data management principles - Experience designing or maintaining data integrations (APIs, connectors, ETL/ELT pipelines) - Strong documentation instincts — you leave systems better-understood than you found them - Comfort operating in ambiguity; this team is new and the roadmap is actively being shaped Preferred - Experience with Marketing Cloud Connect and Synchronized Data Extensions - Knowledge of email deliverability fundamentals (sender reputation, list hygiene, ISP feedback loops) - Exposure to ESP migration or evaluation projects - Familiarity with CDP platforms (Salesforce Data Cloud, Segment, or similar) preferred - Salesforce certification (e.g., Marketing Cloud Email Specialist, Administrator, or Data Cloud) preferred - Experience in a media, publishing, or subscription business preferred The Stack (Today) - CRM: Salesforce Sales Cloud - Marketing Automation: Salesforce Marketing Cloud - Integration: Marketing Cloud Connect - On the roadmap: CDP evaluation and integration, ESP consolidation/migration Compensation: $120-$150K + 10% target bonus Location: New York, NY — hybrid schedule A Few Of Fortune’s Perks And Benefits - 20 vacation days and 2 personal days on top of 11 company holidays and an honour-based sick leave policy - Health, dental, and vision coverage (90% paid for individuals and families), along with flexible spending accounts where Fortune contributes to your HSA - 401(k) plan - Generous parental leave - Dependent care, commuter, and cell phone benefits - Tuition reimbursement program - A commitment to an open, inclusive, and diverse work culture Why Fortune Fortune is one of the world's most recognized business media brands — and we're in an active, well-resourced period of rebuilding our technology and data foundations. This role offers unusual scope: you'll work on problems that matter to the business, with visibility to senior leadership, on a team where your contributions are directly traceable to outcomes.

• Design, develop, maintain, and optimize data pipelines, data services, and data integration solutions within AWS GovCloud environments. • Support migration of legacy data into modernized platform environments. • Develop and maintain APIs, ETL/ELT processes, and file-based integrations with internal and external government systems. • Perform data modeling, database design, schema modifications, and database performance optimization. • Ensure data quality, accuracy, integrity, and consistency across Personnel Vetting Management, Adjudication, and Appeals datasets. • Investigate and resolve data quality issues, coordinate remediation efforts with data providers, and implement preventative data quality controls. • Support data governance activities, data requests, reporting requirements, and audit readiness efforts. • Develop automated data validation, monitoring, and reconciliation processes. • Support database replication, backup/recovery, disaster recovery, and continuity of operations activities. • Collaborate with software engineers, cloud architects, DevSecOps engineers, product owners, and security teams within a SAFe Agile environment. • Support CI/CD pipelines, automated testing, and secure software delivery practices. • Create and maintain technical documentation, data dictionaries, architecture artifacts, and database design documentation. • Support compliance with RMF, Zero Trust, NIST, DoD IL5, and cybersecurity requirements.