Staff Data Engineer

Mesh-AI Limited; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading technology company in London is seeking a Staff Data Engineer to join their Data Platform team. The successful candidate will lead the development of scalable data solutions and own end-to-end projects while collaborating with various teams. Applicants should have at least 6 years of experience, strong skills in AWS, Python, and data warehousing technologies, along with a passion for innovation in the data engineering field. This role provides an excellent opportunity to influence and coordinate significant technical projects in a fast-paced environment.

Qualifications

• 6+ years of experience as a Data Engineer.
• Experience in building scalable data solutions.
• Expert knowledge of data warehousing technologies.
• Proficient in AWS tech stack and version control.

Responsibilities

• Provide hands-on technical leadership for Data Engineering.
• Build new solutions across data products and platform.
• Take ownership of end-to-end projects aligned with business objectives.
• Consult and collaborate with cross-functional teams.

Skills

Data engineering

Python

AWS

SQL

Agile methodologies

DevOps

Kubernetes

Tools

Kafka

Airflow

GitHub Actions

dbt

Job description

Live shows make us feel good. They’re a time to hang with our friends, discover new artists or lose ourselves on a dancefloor. We’re on a mission to bring all of this to more fans, more often – and that’s where you come in.

We’re looking for a Staff Data Engineer to join our rapidly evolving Data Platform team, to help us scale our data platform to make DICE more reliable and impactful for our partners and customers.

At DICE, you’ll be part of the company that’s redefining live entertainment. It’s a place where you can be yourself, influence the culture, and create work that you’re proud of.

About the role

You’re a highly experienced individual who is passionate about building and scaling data products, enhancing data platforms, and comfortable supporting the diverse needs of multiple teams. You’ll be in an inspiring and fast-moving environment working closely with developers, data scientists, data analysts, analytics engineers and product managers. You’ll be leading initiatives and mentoring others to build data products and tools, designing highly scalable systems, and testing theories to arrive at essential insights that will help disrupt a global industry. You will contribute to improving our ways of working and establishing Data Engineering’s goals and best practices across the data team.

We work in an iterative approach, designing, building and trialling out new concepts quickly to test our assumptions and create the best service for our fans & partners. We also continue to pursue the best approaches to the many challenges we face in delivering highly scaled and richly personalised services. We want engineers open to collaboration and who want to be an integral part of the product improvement process.

You’ll be

Providing hands‑on technical leadership to guide and elevate our existing Data Engineering function into a high‑performing team.

Building new solutions across our data products and platform, and leading initiatives to deprecate legacy systems.

Taking full ownership of end‑to‑end projects that are aligned with our business objectives, and planning a clear roadmap with the Engineering Manager and Product Manager for their delivery.

Elevating the team's technical maturity by establishing and championing best practices, overcoming siloed thinking, and fostering cross‑functional collaborations.

Actively consulting and collaborating with the Data Engineering Manager, Product Manager, Analytics Engineers, Data Analysts and Data Scientists to build/architect the most optimal solutions for DICE, and leading the formulation and implementation of a data engineering strategy while acting as a key decision‑maker.

• Owning Data Engineering’s long‑term technical goals, and driving operational efficiency by championing a sustainable, scalable, and cost‑effective architecture across the platform.

You are

Passionate, humble and a proven technical leader.

• Highly autonomous and self‑directed.

Able to tackle ambiguous and unbound technical problems with little guidance.

• Proactively responsible and a systemic problem solver.

Inspiring and collaborative across multi‑disciplinary teams.

Up to date with technologies and techniques, and you know when to use them.

• An established role model and dedicated mentor for other Data Engineers.

You’ll need

Proven experience as a Data Engineer with 6+ years of experience in building solutions, whilst also bringing a strategic outlook ahead.

Experience in building at scale, establishing highly reliable end‑to‑end data solutions with SLAs for both batch and streamed pipelines.

Extensive knowledge and expertise in driving the adoption of data engineering best practices and evidence of successful implementation of the same.

Excellent knowledge of various data warehousing technologies for gathering and consolidating data from multiple sources, including streaming and serving real‑time data.

Expertise in designing and building reliable, scalable solutions with streaming technologies such as Kafka, Kinesis or similar.

Deep architectural knowledge of and hands‑on experience with workflow orchestration software, such as Prefect, Airflow, or similar.

A strong track record applying Agile methodologies, DevOps, CI/CD, Docker/Kubernetes and infrastructure‑as‑Code, e.g. Terraform.

Solid development experience with Python (other programming languages are a plus).

Advanced SQL skills (Relational Querying), e.g. PostgreSQL or similar, and knowledge of NoSQL DBs.

Extensive knowledge of AWS tech stack with a focus on designing cost‑efficient and operationally excellent data solutions.

Expert‑level command of version control and CI workflows (e.g. GitHub Actions), and comfort working in Unix environments.

Experience with a recommendation/personalisation platform.

Experience designing, maintaining, and interfacing with REST APIs.

Knowledge of dbt.

Knowledge of A/B testing or multivariate testing frameworks.

• Experience in deploying data science workflow/MLOps.

Knowledge of data governance, security & privacy, lineage, and quality frameworks in cloud environments.

AWS certifications.

• Experience in adopting AI tools in a responsible manner.

About DICE

DICE is based throughout Europe, North America, Australia and India, and is rapidly growing worldwide. We’re constantly innovating to bring amazing products to fans, artists, venues and promoters.

We know that having a variety of perspectives makes us a better company – it's why we strongly encourage members of underrepresented communities to apply. Find out how we're creating a more diverse, equitable and inclusive DICE.

Application process

Our process usually involves a quick chat on the phone, a portfolio review or task and a couple of interviews where you’ll meet the people you’ll work with. We’ll keep you fully informed along the way.

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