Databricks Engineer

Treliant, LLC
London
1 week ago
Create job alert

Overview

We are looking for Databricks Engineers from a consulting, investment banking or financial services backgrounds to add to our future Talent Pool community. If you wish to be considered for any future roles we have within this area, please share your CV with us.

Treliant is a global consulting firm serving banks, mortgage originators and servicers, FinTechs, and other companies providing financial services. We are led by practitioners from the industry and the regulatory community who bring deep domain knowledge to help our clients drive business change and address the most pressing compliance, regulatory, and operational challenges.

We provide data-driven, technology-enabled advisory and consulting, implementation, staffing and managed services solutions to the regulatory compliance, risk, financial crimes, and capital markets functions of our clients.

Founded in 2005, Treliant is headquartered in Washington, DC, with offices across the United States, London, Belfast, and Łódź, Poland. For more information visit www.treliant.com.

Responsibilities

While the scope of each project may be different, your duties & responsibilities may include:

  • Design and implement Databricks-based solutions for managing, processing, and analyzing large datasets within the financial services sector.
  • Collaborate with cross-functional teams (data scientists, analysts, business stakeholders) to develop and optimize data pipelines, workflows, and data models.
  • Guide and support the migration of legacy systems to Databricks, ensuring seamless transitions from legacy to cloud-based environments.
  • Ensure data integrity, security, and compliance with financial industry regulations.
  • Build and optimize ETL processes using Databricks, Spark, and other data processing tools.
  • Implement data governance best practices within the Databricks environment, including data quality, access controls, and audit logging.
  • Develop real-time data solutions and integrate Databricks with other data platforms (e.g., data lakes, cloud storage, and data warehouses) to ensure seamless data flow.
  • Optimize performance for large-scale data operations, focusing on scalability, efficiency, and cost-effectiveness.

Qualifications

  • Strong educational background – Degree in a relevant field.
  • 2+ years of experience working with Databricks in a production environment.
  • Strong background in ETL/ELT pipeline design and implementation within Databricks.
  • Proficiency in SQL, Python, and PySpark for data processing and analysis.
  • Experience with streaming technologies such as Kafka for real-time data processing.
  • Experience in data migration and integration for data warehouses, including cross-business unit delivery.
  • Strong understanding of data governance, security, and compliance standards in financial services.
  • Knowledge of reference data, including counterparty and business hierarchy data.
  • Experience with financial products (e.g., cashflow forecasting, liquidity management, securities) and regulatory reporting in financial services.
  • Excellent problem-solving, leadership, and communication skills for collaborating with teams and explaining technical concepts to non-technical stakeholders.

Benefits

If you want to be part of a dynamic team of professionals, we invite you to join the team at Treliant. We invest in people, and challenge you to advance your career while achieving your aspirations and goals. Here at Treliant, we pride ourselves on our collaborative team culture, where we embrace diversity of thought and innovation.

Career Development - We put an emphasis on personal and professional growth by providing all the training you’ll need to become a highly skilled Treliant consultant. Programs cover Finance, Regulatory, Technology, and Operational aspects of investment banking.

Clients - As a Treliant consultant, you will be working with some of the top clients in the financial services marketplace such as top tier Investment Banks. Our roles place you at the cutting edge of the projects on which you’ll be working, and giving you the opportunity to learn from, work with and build relationships with the very best within those companies.

Rewards - Treliant offers our permanent staff an excellent total rewards package, including competitive base salary, incentive schemes, flexible healthcare coverage and our company pension scheme.

Core Values - Whether you are a Client or an employee, Treliant wants the best for you. All our relationships are based on our Core Values: Deliver Excellence, Constantly Innovate, Treasure Diversity, Be Nimble, Listen First, and Develop our People.

Right to Work

Treliant isnotin the position to provide sponsorship for this current position and so applicants must be able to work in theUnited Kingdomwithout requiring sponsorship.

#J-18808-Ljbffr

Related Jobs

View all jobs

Databricks Data Engineer

Databricks Data Engineer

Databricks Data Engineer

Databricks Data Engineer

Databricks Data Engineer

Data Engineer - Databricks

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.

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.