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- Tasks: Build and maintain scalable data infrastructure for analytics in a dynamic media buying environment.
- Company: Join Channel Factory, a leader in intelligent marketing solutions for top brands.
- Benefits: Enjoy competitive salary, comprehensive medical benefits, and work-life flexibility.
- Why this job: Shape the future of data architecture while working with cutting-edge technologies.
- Qualifications: 3+ years in data engineering, strong SQL and Python skills, experience with AWS services.
- Other info: Collaborate with a diverse team across multiple time zones and enjoy excellent career growth.
The predicted salary is between 36000 - 60000 £ per year.
Channel Factory provides intelligent marketing solutions that empower brands and agencies to implement, automate, and scale their marketing programs across the world’s largest video library, YouTube, and emerging growth channels. We are passionate about contextual safety, suitability, and performance, and our mission is to help the world’s top brands connect with the right audience in the right context. We are seeking an innovative and dedicated Senior Data Engineer to build, maintain, and evolve scalable data infrastructure that powers our analytics and business intelligence initiatives. This high-impact role will shape the direction of our core data architecture.
Responsibilities
- Collaborate with product managers and business stakeholders to translate complex business requirements into well‑designed, maintainable solutions.
- Implement robust data quality checks, monitoring, and alerting to guarantee the accuracy and timeliness of all data pipelines.
- Create data governance policies and develop optimized data models and schemas for analytical workloads.
- Influence key infrastructure and framework decisions for data pipelining and data management.
- Prioritize, schedule, and deliver complex projects while managing deadlines and deliverables.
- Work effectively with distributed team members across multiple time zones, including offshore development teams.
- Build relationships and foster team cohesion across geographical and cultural boundaries.
- Perform other related tasks as required.
Qualifications
- 3+ years of experience in data engineering or related roles, building and operating scalable data pipelines.
- Experience designing batch and streaming data processing pipelines.
- Strong SQL proficiency in both transactional RDBMS systems and distributed systems.
- Expert-level proficiency in Python.
- In‑depth experience with distributed data technologies such as RabbitMQ, Celery, PySpark.
- In‑depth experience with AWS data services (ECS, EC2, Glue, OpenSearch, RDS).
- Experience with modern Data Lakehouse technologies – Apache Iceberg, S3 Tables, StarRocks.
- Knowledge of digital advertising is a plus.
- Experience integrating data‑science‑based models and algorithms.
- Will occasionally travel for in‑person collaboration, meetings, and trainings.
Benefits
- Competitive salary.
- Comprehensive medical benefits (Medical, Vision, Dental, and Life Insurance).
- Cell phone and Wi‑Fi reimbursement.
- Bill spend stipend.
- Gym stipend.
- Work‑life flexibility – we value your contributions above all.
- Work with a leading startup in a high‑demand industry.
Seniority level: Mid‑Senior. Employment type: Full‑time. Industries: IT Services and IT Consulting.
Data Software Engineer - Media Buying Engineering employer: Channel Factory
Contact Detail:
Channel Factory Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Software Engineer - Media Buying Engineering
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving scalable data pipelines and AWS services. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Be ready to discuss your experience with distributed data technologies and how you've tackled complex data challenges in the past.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Software Engineer - Media Buying Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your data engineering experience, especially with scalable data pipelines and technologies like Python and AWS.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data engineering and how you can contribute to our mission. Share specific examples of past projects that align with the role's responsibilities.
Showcase Your Technical Skills: Don’t shy away from listing your technical proficiencies. Mention your experience with SQL, RabbitMQ, and any relevant data technologies. We want to see how you can influence our data architecture!
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It helps us keep track of applications and ensures you’re considered for the role you’re excited about!
How to prepare for a job interview at Channel Factory
✨Know Your Data Inside Out
Make sure you brush up on your data engineering skills, especially in SQL and Python. Be ready to discuss your experience with building scalable data pipelines and any specific projects you've worked on that relate to the job description.
✨Understand the Company’s Mission
Familiarise yourself with Channel Factory's mission and how they empower brands through intelligent marketing solutions. This will help you align your answers with their goals and show that you're genuinely interested in contributing to their success.
✨Prepare for Technical Questions
Expect to face technical questions about distributed data technologies like RabbitMQ, Celery, and AWS services. Practise explaining complex concepts in simple terms, as you may need to translate technical jargon for non-technical stakeholders.
✨Showcase Your Collaboration Skills
Since the role involves working with distributed teams across multiple time zones, be prepared to share examples of how you've successfully collaborated in similar environments. Highlight your ability to build relationships and foster team cohesion, even from a distance.
