National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Manager, Data Engineering

Optimizely
London
1 month ago
Create job alert

Press Tab to Move to Skip to Content Link

Select how often (in days) to receive an alert: Create Alert

At Optimizely, we're on a mission to help people unlock their digital potential. We do that by reinventing how marketing and product teams work to create and optimize digital experiences across all channels. With Optimizely One, our industry-first operating system for marketers, we offer teams flexibility and choice to build their stack their way with our fully SaaS, fully decoupled, and highly composable solution.

We are proud to help more than 10,000 businesses, including H&M, PayPal, Zoom, and Toyota, enrich their customer lifetime value, increase revenue, and grow their brands. Our innovation and excellence have earned us numerous recognitions as a leader by industry analysts such as Gartner, Forrester, and IDC, reinforcing our role as a trailblazer in MarTech.

At our core, we believe work is about more than just numbers -- it's about the people. Our culture is dynamic and constantly evolving, shaped by every employee, their actions, and their stories. With over 1500 Optimizers spread across 12 global locations, our diverse team embodies the "One Optimizely" spirit, emphasizing collaboration and continuous improvement, while fostering a culture where every voice is heard and valued.

Join us and become part of a company that's empowering people to unlock their digital potential!

To get a sneak peek into our culture, find us on Instagram: @optimizely

In this role, you will be responsible for planning and overseeing the Data Services Data Engineering and Machine Learning teams engaged in enterprise-wide data projects to ensure they are completed in a timely fashion and within budget. You will plan and designate project resources, monitor progress, and keep stakeholders informed the entire way. This role will be supporting the charge in implementing D&A technologies and principles and will act as a single point of contact for data engineering processes to ensure the team is delivering impactful and useful solutions.

Job Responsibilities

  • Leads both operational and directional aspects for the data engineering team
  • Make high-judgement decisions around technology, strategy, execution approach, and personnel
  • Exercise supervision of group in terms of costs, methods, performance, and staffing
  • Accountable for team’s consistent delivery of high quality, on time work; dependencies and impacts have been vetted and mitigated upon final delivery
  • Responsible for employee life cycle, including advising hiring manager by screening and interviewing candidates, onboarding, goal alignment, work assignment, and addressing skill gaps for each team member.
  • Collaborate within and across departments to clear roadblocks, facilitate progress, and enable team to deliver on their commitments
  • Builds team with healthy dynamics
  • Upholds department and company policies and reinforces them when necessary
  • Champion clean, simple, methodical, and ethical data engineering practices
  • Create and maintain optimal data pipeline architecture
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Support the data science team by preparing data for prescriptive and predictive modelling.

Knowledge and Experience

  • 7+ years of experience as a Data Engineer or in a similar role
  • Experience in managing a team of Data Engineers
  • Experience with Data modelling, Data warehousing, and building ETL pipelines
  • Experience with AWS (S3, EKS, EC2, RDS) or similar cloud services, Snowflake, Fivetran, Airbyte, dbt, Docker, Argo
  • Experience in SQL, Python, and Terraform
  • Experience with building Data pipelines and applications to stream and process datasets
  • Robust understanding of DevOps principles is required
  • Experience managing cloud infrastructure would be beneficial
  • Sound knowledge of distributed systems and Data architecture (lambda)- design and implement batch and stream Data processing pipelines, knows how to optimize the distribution, partitioning, and MPP of high-level Data structures
  • Knowledge of Engineering and Operational Excellence using standard methodologies
  • Expertise in designing systems and workflows for handling Big Data volumes
  • Knowledge of Data management fundamentals and Data storage principles
  • Strong problem-solving skills and ability to prioritize conflicting requirements
  • Excellent written and verbal communication skills and ability to succinctly summarize key findings.

Education

Bachelor’s Degree or equivalent work experience

Optimizely is committed to a diverse and inclusive workplace. Optimizely is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Manager, Data Engineering

Assurance - Financial Services - Forensic Data Analytics - Senior Manager - London

Assurance - Financial Services - Forensic Data Analytics - Senior Manager - London

Data Architect (Trading)

Senior Data Manager

Senior Manager - Data Science and Engineering Team

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Data Science Jobs Skills Radar 2026: Emerging Tools, Languages & Platforms to Learn Now

The UK’s data science job market is evolving fast—from forecasting models and AI assistants to real-time decision systems. In 2026, data scientists aren’t just expected to build models—they’re responsible for shaping insights that fuel everything from patient care to predictive banking. Welcome to the Data Science Jobs Skills Radar 2026—your essential annual guide to the languages, tools, and platforms driving demand across the UK. Whether you’re entering the job market or reskilling mid-career, this roadmap helps you prioritise the skills that matter most right now.

How to Find Hidden Data Science Jobs in the UK Using Professional Bodies like the RSS, BCS & More

The data science job market in the UK is thriving—but also increasingly competitive. As organisations in finance, healthcare, retail, government, and tech accelerate digital transformation, the demand for data talent has soared. Yet many of the best data science jobs are never posted publicly. They’re shared behind closed doors—within professional networks, at invite-only events, or through member-only mailing lists and specialist interest groups. These “hidden” roles are often filled through referrals, collaborations, or direct outreach to trusted experts. In this guide, we’ll show you how to unlock these hidden opportunities by engaging with key UK professional bodies such as the Royal Statistical Society (RSS), BCS (The Chartered Institute for IT), and Turing Society, plus communities like PyData and AI UK. You’ll learn how to use directories, CPD events, and networks to move beyond job boards—and into roles where you’re approached, not just applying.

How to Get a Better Data Science Job After a Lay-Off or Redundancy

Redundancy can be tough to face, especially in a competitive field like data science. But it’s important to know: your experience, analytical thinking, and modelling skills are still in demand. Across sectors like healthcare, finance, e-commerce, government and AI startups, UK employers continue to seek data scientists who can deliver value through insight, prediction, and automation. This guide will walk you through how to bounce back from redundancy with purpose and clarity—whether you're a data analyst looking to step up, a mid-level data scientist, or a machine learning specialist seeking a better-aligned opportunity.