Simon & Schuster is a global leader in general interest publishing, dedicated to providing the best in fiction and nonfiction for readers of all ages, and in all printed, digital, and audio formats. Its distinguished roster of authors includes many of the world’s most popular and widely recognized writers, and winners of the most prestigious literary honors and awards. It is home to numerous well-known imprints and divisions such as Simon & Schuster, Scribner, Atria Books, Gallery Books, Pocket Books, Adams Media, Simon & Schuster Children’s Publishing and Simon & Schuster Audio and international companies in Australia, Canada, India, and the United Kingdom, and proudly brings the works of its authors to readers in more than 200 countries and territories. For more information visit our website at www.simonandschuster.com.

The Role
Simon & Schuster is investing in Data & Decision Intelligence to build a decision ecosystem where data, tools, and automation are embedded in everyday work, enabling faster and better-informed decisions. The Director, Data Platform & Engineering will turn that commitment into a secure, scalable, and AI-ready enterprise data platform. This leader will own the platform and engineering roadmap, build the team and operating model, and partner across Technology and the business to modernize fragmented data and manual processes without disrupting critical operations.
What You Will Do

- Own the enterprise data platform. Define and execute the architecture and roadmap for ingestion, storage, transformation, orchestration, serving, metadata, lineage, and data quality across global data domains.
- Build the engineering organization. Hire, lead, and develop a globally distributed team; clarify roles, capacity, delivery practices, and career paths while raising technical and leadership standards.
- Modernize with continuity. Rationalize legacy pipelines, reporting dependencies, and disconnected workflows; establish migration plans that protect daily business operations and reduce technical debt.
- Create trusted foundations. Partner with data governance, business, and technology leaders to establish documented systems of record, shared data definitions, ownership, and reusable data products.
- Set engineering standards. Establish practical standards for architecture, modeling, testing, documentation, CI/CD, infrastructure as code, security, privacy, observability, incident response, and disaster recovery.
- Enable strategic data products. Partner with Analytics Engineering, Data Science, Product, and business teams to support enterprise forecasting,



production and warehouse planning, author and title discovery, backlist optimization, marketing effectiveness, and finance.
- Advance automation and responsible AI. Replace repetitive, data-intensive processes with reliable automation and ensure governed, well-documented data is available for AI-enabled applications, with appropriate human oversight and controls.
- Operate for reliability and value. Define service expectations and measures for availability, freshness, quality, delivery speed, adoption, and cost; continuously improve platform performance and business outcomes.
- Lead investment and partnerships. Shape budgets, capacity plans, vendor strategy, and consulting engagements; communicate tradeoffs and recommendations clearly.

What You Bring

- Leadership experience. 10+ years in data engineering, platform engineering, or related roles, including 4+ years leading engineering teams and senior technical talent; experience managing managers is preferred.
- Enterprise platform ownership. A record of defining and delivering cloud data-platform strategy, architecture, modernization roadmaps, and operating models across multiple functions or data domains.
- Technical credibility. Strong working knowledge of SQL, Python, data modeling, distributed data systems, cloud warehouses or lakehouses, transformation frameworks, ingestion and orchestration patterns, APIs, and software-engineering practices.
- Modern delivery discipline. Experience with Git-based development, automated testing, CI/CD, infrastructure as code, data observability, metadata and lineage, security, privacy, and production support.
- Transformation leadership. Demonstrated success migrating legacy data ecosystems while managing dependencies, change, service continuity, and stakeholder expectations.
- Business and executive partnership. Ability to translate enterprise priorities into a sequenced roadmap, make sound build-versus-buy decisions, and communicate architecture, risk, cost, and value in clear business terms.
- Financial and vendor management. Experience managing platform spend, capacity, vendors, contracts, and consulting partners with a focus on measurable value and sustainable total cost.
- People leadership.



A record of attracting, developing, and retaining diverse talent and building a culture of accountability, collaboration, pragmatic engineering, and continuous improvement.

Preferred

- Relevant platforms. Experience with Snowflake and/or BigQuery, dbt, modern ingestion tools, semantic layers, data catalogs, and BI or analytics platforms.
- AI-ready data. Experience enabling machine learning, generative AI or decision-support products using governed enterprise data.
- Industry context. Publishing, media, retail, consumer products, forecasting, or supply-chain experience; bachelor's degree in a technical or quantitative field, or equivalent practical experience.

How Success Will Be Measured

- A clear enterprise roadmap. The target architecture, investment plan, ownership model, and delivery sequence are understood and supported across Data, Technology, and the business.
- A dependable, governed platform. Core data products meet defined expectations for quality, freshness, availability, lineage, security, and cost.
- Modernization with measurable value. Priority legacy workflows and manual processes are retired or improved without business disruption, with gains in speed, accuracy, control, or employee capacity.
- A strong engineering organization. The team, standards, and operating model can sustainably deliver enterprise priorities and support responsible AI at scale.

An Inclusive Workplace
We welcome candidates with different paths and perspectives. If you do not meet every preferred qualification, we still encourage you to apply.

Simon & Schuster India is an equal opportunity employer (EOE). At Simon & Schuster India, the spirit of inclusion feeds into everything that we do. From employee benefits/programs and social impact outreach initiatives, we believe that opportunity, access, resources, and rewards should be available to and for the benefit of all. Simon & Schuster India is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, and Veteran status.

Candidates hired for this or any other posted Simon & Schuster India role will be employees of Simon & Schuster Publishers India Private Limited, subject to all policies, including the Workplace Privacy Notice, and eligible solely for the advantages plans thereof.

📌 Director Data Platform & Engineering (Noida)
🏢 Simon & Schuster
📍 Noida