Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics
Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics

Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics

Full-Time 80000 - 100000 £ / year (est.) No home office possible
JPMorgan Chase

At a Glance

  • Tasks: Lead data analytics projects and deliver insights that drive strategic decisions.
  • Company: Join JPMorgan Chase, a leading global financial institution with a rich history.
  • Benefits: Enjoy competitive pay, health coverage, tuition reimbursement, and wellness support.
  • Other info: Collaborative environment with opportunities for mentorship and career growth.
  • Why this job: Make a real impact in technology analytics while working with cutting-edge tools.
  • Qualifications: 7+ years in data analytics; strong statistical and software engineering skills required.

The predicted salary is between 80000 - 100000 £ per year.

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you've come to the right place. As a Principle Software Engineer at JPMorganChase within the Global Technology - Analytics, Insights and Measurements (GT AIM) team, you will deliver trusted, decision-grade insight across GT through rigorous statistical analysis and domain-informed interpretation. You will be entrusted in delivering market-leading technology products in a secure, stable, and scalable way.

As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. Reporting to the Head of GT Architecture and Strategy (GTAS), this role applies sound statistical and analytical methods to technology data to inform strategy, execution, and investment decisions across multiple technology domains. The role works in close partnership with leaders of strategic programs, providing continuous statistical analysis and insight to support priority outcomes.

The role requires deep understanding of software engineering delivery models and flows e.g., feature branch, trunk-based, and integrated delivery to ensure metrics and analysis accurately reflect how technology is delivered. Areas of focus include developer productivity, delivery and portfolio performance, technology spend and value realization, return on investment, and the adoption and impact of Artificial Intelligence across GT. The emphasis is on building internally owned, transparent, and explainable analytics through sound statistical methods, rather than relying on opaque third-party tools. All roles are hands-on. Managers provide leadership and direction while actively contributing to analysis and insight delivery. Senior Individual Contributors independently own complex analytical problems and influence outcomes through expertise and insight.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

Insights, Communications and Reporting

Define, create, deliver, establish and maintain a metrics framework and complementary visuals aligned to CTO and technology leadership decision needs. Your framework will be inclusive of many different technology initiatives, including emerging capabilities such as Artificial Intelligence (AI), Software Engineering, Portfolio Management and more. Build strong relationships across various GT functions. Communicate statistical findings effectively to technical and non-technical audiences without oversimplification or false precision. Narratives and analyses need to be clear. They need to articulate what is happening, why it is happening, and how confident the conclusions are. Work closely to JPMC key strategic programs and initiatives, while providing continuous analysis & insights to support their priority outcomes, all with sound statistical measures. Your insights must explain performance, trends, variability, and drivers across all of GT. Lead, coach and develop a small team of highly skilled, impactful analytics professionals. Manage corresponding standards for statistical rigor, transparency and clarity.

Statistical Analysis and Data Interpretation

Continuously refine analytical approaches as technology strategy, architecture, and delivery practices evolve. Support technology leadership in understanding trade-offs, risks, opportunities, and uncertainty. Conclusions provided must be sound, statistically and contextually valid and based on actual engineering and business ecosystems. Collaborate closely with engineering, platform, architecture, and AI enablement teams to understand delivery practices, workflows and constraints. Perform hands-on statistical analysis using appropriate descriptive, inferential, and exploratory techniques. Apply those techniques and reasoning to assess variability, confidence, uncertainty, statistical significance, and margin of error where appropriate. Evaluate distributions, trends, and changes over time while accounting for structural differences in teams, systems, and delivery models. Be able to distinguish correlation from causation and clearly communicate analytical limitations, assumptions, and confidence levels.

Operations, Measurements and Instrumentation

Identify required data points needed to answer key analytical and statistical questions, then define requirements for instrumenting data at the source. Ensure metrics are compatible with different engineering flows, including feature branch development, trunk-based development, and integrated delivery. Improve data quality, consistency, and traceability over time. Maintain clear documentation of metric definitions, statistical methods, and calculation logic. Ensure reporting supports informed decision-making rather than metric consumption without context.

Required qualifications, capabilities, and skills
  • Degree in Mathematics, Statistics, Data Science, Engineering, Computer Science or equivalent
  • 7+ years applicable work experience.
  • 10+ years experience performing statistical analytics, data science, or performance measurement roles.
  • Practical experience working with technology, delivery, portfolio, financial, or AI-related data.
  • Demonstrated experience applying statistical methods to real-world, imperfect datasets and evolving delivery practices.
  • Strong familiarity with concepts such as statistical significance, confidence intervals, variability, and margin of error, and when their use is appropriate.
  • Proficiencies in a modern data stack. This includes Excel, Python, R Studio, Power BI, Tableau, Qlik, SQL, Python, dbt, Databricks, Snowflake, and Microsoft Fabric, alongside specialized portfolio and spend analytics tools like Apptio.
  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
  • Experience influencing senior technology leaders and guiding decision-making.
Preferred qualifications, capabilities, and skills
  • Desire and ability to mentor peers through statistical expertise and engineering domain knowledge.
  • Strong formal training in statistics.
  • Intellectual curiosity and commitment to statistical rigor.
  • Respect for the complexity and variability of software delivery systems within a large enterprise.
  • Practical cloud native experience.
  • Proficiency in automation and continuous delivery methods (CI/CD pipelines).
  • Practical understanding of software engineering delivery models, including but not limited to feature branch, trunk-based, and integrated delivery.
  • Experience leading or mentoring analytics professionals.

JPMorganChase, one of the oldest and most trusted financial institutions, provides innovative solutions to millions of consumers, small businesses, and many of the world's most prominent corporate, institutional, and government clients. Our history spans over 200 years, and today we lead in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined by role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits to meet employee needs, including comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal-opportunity employer and place a high value on diversity and inclusion. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also provide reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.

Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics employer: JPMorgan Chase

At JPMorgan Chase, we pride ourselves on being a leading financial institution that fosters a dynamic and inclusive work environment. As a Lead Data Analytics Engineer, you will benefit from our commitment to employee growth through mentorship opportunities, comprehensive health benefits, and a competitive rewards package. Our culture encourages innovation and collaboration, allowing you to make a meaningful impact while working alongside some of the brightest minds in the industry.
JPMorgan Chase

Contact Detail:

JPMorgan Chase Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics

✨Tip Number 1

Network like a pro! Reach out to folks in your desired field, especially those at JPMorganChase. A friendly chat can open doors and give you insights that job descriptions just can't.

✨Tip Number 2

Prepare for interviews by practising common questions related to data analytics and software engineering. We recommend using the STAR method (Situation, Task, Action, Result) to structure your answers and showcase your skills effectively.

✨Tip Number 3

Showcase your analytical prowess! Bring examples of your past work or projects that highlight your statistical analysis skills. This will help you stand out and demonstrate your hands-on experience.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of the JPMorganChase team.

We think you need these skills to ace Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics

Statistical Analysis
Data Interpretation
Analytical Skills
Software Engineering Delivery Models
Statistical Methods
Data Quality Improvement
Communication Skills
Python
R Studio
SQL
Power BI
Tableau
Cloud Native Experience
CI/CD Pipelines
Mentoring and Coaching

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter to highlight the skills and experiences that align with the Lead Data Analytics Engineer role. We want to see how your background fits into our vision at StudySmarter!

Showcase Your Analytical Skills: Since this role is all about data and analytics, don’t shy away from showcasing your statistical prowess. Use specific examples of how you've applied analytical methods in past projects to solve real-world problems.

Be Clear and Concise: When writing your application, clarity is key! We appreciate straightforward narratives that articulate your achievements and insights without unnecessary jargon. Remember, we want to understand your thought process easily.

Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it’s super easy!

How to prepare for a job interview at JPMorgan Chase

✨Know Your Stats

Brush up on your statistical methods and be ready to discuss how you've applied them in real-world scenarios. Be prepared to explain concepts like confidence intervals and statistical significance, as these will likely come up during the interview.

✨Showcase Your Technical Skills

Make sure you can demonstrate your proficiency with tools like Python, SQL, and Power BI. Bring examples of past projects where you used these technologies to solve complex problems or improve processes, as this will show your hands-on experience.

✨Communicate Clearly

Practice explaining your analytical findings in a way that both technical and non-technical audiences can understand. Use clear narratives to articulate what your data shows and why it matters, as effective communication is key in this role.

✨Build Relationships

Highlight your ability to collaborate with different teams. Discuss any experiences where you’ve worked closely with engineering or leadership teams to drive insights and decisions, as building strong relationships is crucial for success in this position.

Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics
JPMorgan Chase

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