Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build real-time data pipelines and implement innovative data architectures for clients.
- Company: Join a leading tech firm with a global presence and a creative culture.
- Benefits: Enjoy competitive salary, health benefits, remote work options, and continuous learning opportunities.
- Why this job: Make a real impact by transforming data into actionable insights and solutions.
- Qualifications: 5+ years in data engineering, strong SQL and Spark skills, and consulting experience preferred.
- Other info: Dynamic team environment with excellent career growth and professional development.
The predicted salary is between 48000 - 72000 £ per year.
Simple Machines UK – Job Ad – Senior Data Engineer
Position: Senior Data Engineer
Location: London, United Kingsom
Simple Machines. Data Engineered to Life
Simple Machines is a leading independent boutique technology firm with a global presence, including teams in London, Sydney, San Francisco, and New Zealand. We specialise in creating technology solutions at the intersection of data, AI, machine learning, data engineering, and software engineering. Our mission is to help enterprises, technology companies, and governments better connect with and understand their organisations, their people, their customers, and citizens. We are a team of creative engineers and technologists dedicated to unleashing the potential of data in new and impactful ways. We design and build bespoke data platforms and unique software products, create and deploy intelligent systems, and bring engineering expertise to life by transforming data into actionable insights and tangible outcomes.
We engineer data to life.
The Role:
The Senior Data Engineer at Simple Machines is a dynamic, hands-on role focused on building real-time data pipelines and implementing data mesh architectures to enhance client data interactions. This position blends deep technical expertise in modern data engineering methods with a client-facing consulting approach, enabling clients to effectively manage and utilise their data. Within a team of top-tier engineers, the role involves developing greenfield data solutions that deliver tangible business outcomes across various environments.
Technical Responsibilities
- Developing Data Solutions: Implement and enhance data-driven solutions integrating with clients\’ systems using state-of-the-art tools such as Databricks, Snowflake, Google Cloud, and AWS. Embrace modern data architecture philosophies including data products, data contracts, and data mesh to ensure a decentralized and consumer-oriented approach to data management.
- Data Pipeline Development: Develop and optimise high-performance, batch and real-time data pipelines employing advanced streaming technologies like Kafka, and Flink. Utilise workflow orchestration tools such as Dataflow and Airflow.
- Database and Storage Optimization: Optimize and manage a broad array of database technologies, from traditional relational databases (e.g., PostgreSQL, MySQL) to modern NoSQL solutions (e.g., MongoDB, Cassandra). Focus on strategies that enhance data accessibility, integrity, and performance.
- Big Data Processing & Analytics: Utilise big data frameworks such as Apache Spark and Apache Flink to address challenges associated with large-scale data processing and analysis. These technologies are crucial for managing vast datasets and performing complex data transformations and aggregations.
- Cloud Data Management: Implement and oversee cloud-specific data services including AWS Redshift, S3, Google BigQuery, and Google Cloud Storage. Leverage cloud architectures to improve data sharing and interoperability across different business units.
- Security and Compliance: Ensure all data practices comply with security policies and regulations, embedding security by design in the data infrastructure. Incorporate tools and methodologies recommended for data security and compliance, ensuring robust protection and governance of data assets.
Consulting Responsibilities
- Client Advisory: Provide expert advice to clients on optimal data practices that align with their business requirements and project goals.
- Training and Empowerment: Educate client teams on the latest technologies and data management strategies, enabling them to efficiently utilise and maintain the solutions we have developed.
- Professional Development: Keep up with the latest industry trends and technological advancements, continually upgrading skills and achieving certifications in the technologies Simple Machines implements across its client base.
Ideal Skills and Experience
- Core Data Engineering Tools & Technologies: Demonstrates proficiency in SQL and Spark, and familiarity with platforms such as Databricks and Snowflake. Well-versed in various storage technologies including AWS S3, Google Cloud BigQuery, Cassandra, MongoDB, Neo4J, and HDFS. Adept in pipeline orchestration tools like AWS Glue, Apache Airflow, and dbt, as well as streaming technologies like Kafka, AWS Kinesis, Google Cloud Pub/Sub, and Azure Event Hubs.
- Data Storage Expertise: Knowledgeable in data warehousing technologies like BigQuery, Snowflake, and Databricks, proficient in managing various data storage formats including Parquet, Delta, ORC, Avro, and JSON to optimise data storage and retrieval.
- Building and Managing Large-scale Data Systems: Experienced in developing and overseeing large-scale data pipelines and data-intensive applications within production environments.
- Data Modelling Expertise: Proficient in data modelling, understanding the implications and trade-offs of various methodologies and approaches.
- Infrastructure Configuration for Data Systems: Competent in setting up data system infrastructures, favouring infrastructure-as-code practices using tools such as Terraform and Pulumi.
- Programming Languages: Proficient in Python and SQL, with additional experience in programming languages like Java, Scala, GoLang, and Rust considered advantageous.
- CI/CD Implementation: Knowledgeable about continuous integration and continuous deployment practices using tools like GitHub Actions and ArgoCD, enhancing software development and quality assurance.
- Testing Tools and Frameworks: Experienced with data quality and testing frameworks such as DBT, Great Expectations, and Soda, ensuring the reliability of complex data systems.
- Commercial Application of Data Engineering Expertise: Demonstrated experience in applying data engineering skills across various industries and organisations in a commercial context.
- Agile Delivery and Project Management: Skilled in agile, scrum, and kanban project delivery methods, ensuring efficient and effective solution development.
- Consulting and Advisory Skills: Experienced in a consultancy or professional services setting, offering expert advice and crafting customised solutions that address client needs. Effective in engaging stakeholders and translating business requirements into practical data engineering strategies.
Professional Experience and Qualifications
- Professional Experience: At least 5+ years of data engineering or equivalent experience in a commercial, enterprise, or start-up environment. Consulting experience within a technology consultancy or professional services firm is highly beneficial.
- Educational Background: Degree or equivalent experience in computer science or a related field.
#J-18808-Ljbffr
Senior Data Platforms Engineer employer: Internetwork Expert
Contact Detail:
Internetwork Expert Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Platforms Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or tech conferences where you can meet potential employers and fellow data enthusiasts. Remember, sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines or cloud services. This gives you a chance to demonstrate your expertise in tools like Databricks or AWS, making you stand out to recruiters.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with data engineering tools and how you've solved real-world problems. Practising common interview questions can help you feel more confident.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application reflects your passion for data engineering and your unique skill set.
We think you need these skills to ace Senior Data Platforms Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Data Engineer role. Highlight your expertise in data engineering tools like SQL, Spark, and cloud platforms. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data engineering and how your background fits with our mission at Simple Machines. Be genuine and let your personality come through.
Showcase Your Projects: If you've worked on any relevant projects, whether personal or professional, make sure to mention them. We love seeing real-world applications of your skills, especially if they involve building data pipelines or optimising databases.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you'll be one step closer to joining our dynamic team of engineers at Simple Machines!
How to prepare for a job interview at Internetwork Expert
✨Know Your Tech Stack
Make sure you’re well-versed in the specific tools and technologies mentioned in the job description, like SQL, Spark, Databricks, and Snowflake. Brush up on your knowledge of data pipelines and cloud services, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss real-world scenarios where you've tackled complex data challenges. Think about how you’ve optimised data systems or improved data accessibility in previous roles. This will demonstrate your hands-on experience and ability to deliver tangible outcomes.
✨Understand Their Business
Research Simple Machines and their clients to understand their mission and the industries they serve. Being able to articulate how your skills can help them achieve their goals will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current projects, team dynamics, or how they approach data security and compliance. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
