At a Glance
- Tasks: Lead a data engineering squad to deliver high-quality data platforms and innovative solutions.
- Company: Join Moody's, a leading company in data-driven insights and analytics.
- Benefits: Enjoy competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and leverage AI tools for enhanced productivity.
- Why this job: Make an impact by driving data quality and governance in a dynamic environment.
- Qualifications: 5+ years in product management or data engineering; strong agile and analytical skills.
The predicted salary is between 70000 - 90000 € per year.
The Data Platform Product Manager leads a data engineering squad that builds and operates core data platforms, prioritising rapid, reliable delivery of new data sets while upholding high standards for data quality, controls, and governance. This role is part of the Data Product Management Team, a dynamic, analytical group focused on delivering customer and business value through data.
Key Responsibilities
- Own a data engineering squad, accountable for roadmap planning, execution, and delivery.
- Drive effective delivery by accelerating decision‑making, removing blockers, and keeping the team focused on the highest‑value outcomes for customers and the business.
- Partner with the Data Platform Product Owner, Data Governance, Quality Assurance, Data Engineering, and internal Product Development teams to bring new data sets to market.
- Collaborate closely with data engineers to understand solution complexity, evaluate architectural trade‑offs, and select implementation approaches that balance speed, scalability, cost, and AI readiness.
- Manage agile ceremonies and execution (sprint planning, backlog refinement, reviews, retrospectives) to ensure consistent, high‑quality delivery.
- Facilitate alignment across data and product development squads to manage dependencies and enable sound decision‑making.
- Own and prioritise a backlog consisting of user stories, defects, refactors, infrastructure work, and production support, prioritised by business value, platform reuse, risk reduction, and AI enablement.
- Use AI and GenAI tools in day‑to‑day product management, including:
- Accelerating creation, refinement, and validation of product requirements, user stories, and acceptance criteria.
- Summarising stakeholder input, data issues, incidents, and operational metrics to inform prioritisation decisions.
- Supporting impact analysis and root‑cause exploration for data quality or delivery issues.
- Identify opportunities to automate and augment data delivery workflows, including data quality validation, documentation, metadata management, and operational reporting.
- Coordinate release readiness and deployment with Release Management, Operations, Data Quality, and Data Governance partners.
- Build strong relationships with data strategy and business stakeholders to drive delivery of new data sets and the evolution of existing data assets.
- Embed data quality, lineage, and governance standards directly into backlog items and acceptance criteria, with particular focus on data used by AI and model‑driven products.
- Proactively identify and mitigate delivery, quality, privacy, and operational risks throughout the data lifecycle, particularly where AI usage increases sensitivity, scale, and downstream impact.
Qualifications
- Bachelor’s degree required; advanced degree (MBA, Master’s) a plus.
- 5+ years of experience in technical product management or data engineering for data‑intensive B2B products.
- Strong grasp of agile methodologies and delivery practices.
- Prior experience in data platform, data warehousing, or analytics environments (e.g., Snowflake, Databricks, Redshift, Athena, Kafka).
- Experience defining, monitoring, and operationalising data quality/QA standards, especially for downstream analytics or AI consumers.
- Experience using AI or Generative AI tools to improve productivity in product management, including requirements authoring, analysis, summarisation, and decision support.
- Proficiency with SQL for data analysis, troubleshooting, and validation.
- Familiarity with how data is used by machine learning or AI systems, even if not directly building models.
- Results‑oriented and action‑focused, with experience driving delivery in complex, matrixed environments.
- Experience working in matrixed organisations, including teams supported by vendors or external partners.
- Strong communication skills with the ability to translate complex data and platform concepts for technical and non‑technical stakeholders.
- Strong analytical skills, persistence in problem‑solving, and attention to detail.
- Demonstrated initiative, curiosity, and commitment to continuous improvement.
- A track record of improving team and organisational effectiveness through influence and scalable processes.
Associate Director - Data Platform Product Manager in Salford employer: Moody's Investors Service
At Moody's, we pride ourselves on being an exceptional employer, offering a collaborative and innovative work culture that empowers our employees to thrive. As an Associate Director - Data Platform Product Manager, you will have the opportunity to lead a dynamic data engineering squad, driving impactful projects while benefiting from continuous professional development and a commitment to diversity and inclusion. Our location fosters a vibrant community, providing access to cutting-edge resources and a supportive environment that values your contributions and encourages growth.
StudySmarter Expert Advice🤫
We think this is how you could land Associate Director - Data Platform Product Manager in Salford
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or a project that highlights your data management expertise. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to data platforms. We all know that confidence is key, so the more you rehearse, the better you'll perform!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing familiar faces!
We think you need these skills to ace Associate Director - Data Platform Product Manager in Salford
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in data engineering and product management. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Showcase Your Agile Experience:Since this role involves managing agile ceremonies, it’s crucial to demonstrate your familiarity with agile methodologies. Share specific examples of how you've successfully led teams or projects using these practices.
Highlight Data Quality Skills:Given the emphasis on data quality and governance, be sure to mention any experience you have in defining and operationalising data quality standards. We love seeing candidates who understand the importance of data integrity!
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role without any hiccups!
How to prepare for a job interview at Moody's Investors Service
✨Know Your Data Inside Out
Make sure you’re well-versed in the data platforms and tools mentioned in the job description, like Snowflake or Databricks. Brush up on your SQL skills too, as you'll likely need to demonstrate your ability to analyse and validate data during the interview.
✨Showcase Your Agile Expertise
Since this role involves managing agile ceremonies, be prepared to discuss your experience with agile methodologies. Share specific examples of how you've facilitated sprint planning or retrospectives, and how these practices have led to successful project outcomes.
✨Highlight Collaboration Skills
This position requires strong collaboration with various teams. Think of instances where you’ve partnered with data engineers or product owners to deliver high-value outcomes. Be ready to explain how you’ve navigated complex team dynamics to achieve results.
✨Demonstrate Your Problem-Solving Mindset
Prepare to discuss challenges you've faced in previous roles, particularly around data quality or delivery issues. Highlight your analytical skills and persistence in problem-solving, and how you’ve proactively identified and mitigated risks in data projects.
