Director of Data Engineering

JPMorgan Chase & Co.
Glasgow
2 months ago
Create job alert

As a Director of Software Engineering at JPMorgan Chase within the Corporate Technology, Regulatory Reporting Team, you will be at the helm of a technical area, influencing teams, technologies, and projects across various departments. Your extensive understanding of software, applications, technical processes, and product management will be instrumental in steering multiple complex projects and initiatives. As the primary decision maker for your teams, you will be a catalyst for innovation and solution delivery.

You are an integral part of an agile team that works to enhance, build, and deliver trusted 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 areas within various business functions in support of the firm’s objectives. You will be responsible to build & transform data strategy to ensure data is being consumed and leveraged within the ecosystem of the application suite appropriately. Data processing pipelines that includes setting, leveraging data models & entities in data lake environment (on-prem or AWS), data sourcing, ingestion, enrichment and business reporting, build or enhance data analytics and reporting solutions are using technologies like Databricks, Python, Java, various in-house applications & public cloud platforms(AWS) services & BI tools like Tableau, Cognos, Alteryx 

Job responsibilities 

Obtain formal training or certification on Databricks concepts and expert applied experience. In addition, advanced experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise Defining Data strategy, consumption pattern, data lineage and contracts. Working with senior business/tech stakeholders on consumption patterns and SLA's including Op model for different asset class dataset Lead the initiatives to setup and leverage data models & entities in data lake environment (internal and public cloud like AWS), Build data pipelines that includes sourcing information, writing logic for ingestion, enrichment and business analytics and reporting Integrate data pipeline with analytical and reporting tools ( includes Tableau, Cognos, Alteryx and Java based applications), Customize GAIA and Public Cloud(AWS) based UI/UX applications (Add new reporting workflows or Enhance existing leveraging Core Java, Java scripting, Mongo DB etc)  Perform data analysis, performance tuning and issue investigations (on databases, Databricks, Big data and Cloud platforms. Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations Create tools for automation, business logic generation, testing and data reconciliation. Participate in design discussion and code reviews  Delivers technical solutions that can be leveraged across multiple businesses and domains, executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Develops secure high-quality production code, and reviews and debugs code written by others. Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Influences peer leaders and senior stakeholders across the business, product, and technology teams and leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies. Champions the firm’s culture of diversity, equity, inclusion, and respect.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering, SDLC concepts and expert applied experience. In addition, advanced experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise. Hands-on practical experience delivering system design, application development, testing, and operational stability Extensive hands-on development industry experience and in-depth knowledge of Databricks (including DLT), databases (Oracle or DB2 or Sybase), any Query Language like PL/SQL, Domain specific Language (DSL) and in data modeling (This is most important skill requirement for this role) Proficiency in automation and continuous delivery methods with deep understanding/ practical know how on the importance of Regression Testing & Code Coverage etc.  Advanced understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (., cloud, artificial intelligence, machine learning, mobile, Practical cloud native experience. Experience developing or leading cross-functional teams of technologists Experience with hiring, developing, and recognizing talent Experience leading a product as a Product Owner or Product Manager

Preferred qualifications, capabilities, and skills 

Experience working at code level In-depth knowledge of the financial services industry and their IT systems ( Exposure to Regulatory reporting domain will be preferable) Knowledge of Kafka, Spark and Scala , Kubernetes will be preferred

Related Jobs

View all jobs

Director of Data Engineering

Head of Data Engineering - Product & Plan for Better

Head of Data Engineering - Product & Plan for Better (Basé à London)

Director of Data Science

Analytics Director - Data Science

Apply Now! Solution Data Architect ...

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.