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For Companies At a Glance
- Tasks: Build and maintain data platforms, pipelines, and internal tools for customer analytics.
- Company: Join HENI, a cutting-edge art services business merging art and technology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make an impact in the art world by leveraging data to drive decisions.
- Qualifications: Strong Python skills and experience with data engineering and analytics.
- Other info: Dynamic team environment with exciting projects and career advancement potential.
The predicted salary is between 50000 - 70000 ÂŁ per year.
About Us
HENI is an international art services business working with leading artists and estates across printmaking, marketplaces for physical artworks, NFTs, publishing, digital, video production, art research and analysis. HENI is at the cutting edge of art and tech using the latest and best technologies, to make art accessible to audiences worldwide.
Position Overview Summary
We are looking for a Software Engineer to join our Data team. You will build and maintain the data platform that powers customer analytics — pipelines, internal tools, and integrations — while contributing to analytical work that supports commercial teams and C‑suite decision‑making. You will also play a key role in broader data initiatives across the organisation, working with the wider team to shape and deliver many diverse projects.
Key Responsibilities
- Data Engineering & Platform
- Build and maintain data pipelines
- Develop internal data applications using Streamlit or Dash for ad‑hoc analysis and customer research
- Implement data quality checks and validation to ensure pipeline reliability
- Support data architecture decisions and contribute to broader data platform improvements
- Integrate third‑party data sources (e.g. HubSpot, Facebook Business) into the customer data platform
- Respond to ad‑hoc data requests from across the business
- Contribute to HENI News data initiatives
- Customer Analytics
- Write analytic SQL queries to support accounts and client liaison teams
- Build and maintain dashboards in Apache Superset for self‑serve business intelligence
- Support the creation of Customer Data Reports for C‑suite stakeholders
- Contribute to customer analytics: segmentation, retention analysis, and behavioural insights
Required Technical Skills
- Software Engineering
- Strong Python skills — the primary language for all data work
- Git and version control workflows
- Automated testing: unit tests, integration tests, and data quality tests
- Writing clean, maintainable, well‑structured code
- Experience building and maintaining production applications or services
- Data Processing
- Experience with distributed data processing frameworks (e.g. PySpark, Spark SQL)
- pandas and numpy for data manipulation and analysis
- SQL for analytical queries and database interaction
- Cloud & Infrastructure
- Experience with cloud‑based data pipeline tools (e.g. AWS Glue, Azure Data Factory, GCP Dataproc)
- Familiarity with cloud object storage (e.g. S3, GCS, Azure Blob) and columnar data formats (e.g. Parquet)
- Familiarity with Infrastructure as Code, containerization (Docker), CI/CD
- Experience with container orchestration (e.g. Kubernetes, Docker swarm, AWS ECS)
- Visualisation & Reporting
- Experience with BI/dashboarding tools (e.g. Superset, Looker, Metabase)
- Experience building internal data tools or apps (e.g. Streamlit, Dash)
Nice-to-Have Skills
- Experience with statistical modelling and/or machine learning (e.g. scikit‑learn, scipy)
- Experience with CRM/marketing platform APIs (e.g. HubSpot, Salesforce or similar)
- Experience integrating LLM APIs (e.g. Gemini/Vertex AI, OpenAI/ChatGPT) to build sophisticated data products
- Experience with data quality frameworks (e.g. Great Expectations or similar)
Our Stack
- AWS (S3, RDS, Glue, ECS, EC2)
- Airbyte, Apache Airflow
- Streamlit, Apache Superset
- Delta Lake, PostgreSQL
- Docker, Kubernetes, AWS CDK
- Git
Programming Languages
- Python (primary)
- SQL (strong)
Education & Experience
- Master’s degree in Computer Science, Software Engineering, Data Science, Engineering or a related quantitative discipline
- 2‑3 years of industry experience in a software engineering, data engineering, or similar technical role
- Experience working with data pipelines
- Comfortable working across the full stack from data ingestion through to internal tools and dashboards
- Experience presenting technical work to non‑technical stakeholders
- Able to work autonomously while coordinating with a small data team
Software Engineer - Data employer: HENI
Contact Detail:
HENI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer - Data
✨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 projects, especially those related to data engineering and analytics. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and practising common interview questions. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨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, it shows you’re genuinely interested in joining our team at HENI.
We think you need these skills to ace Software Engineer - Data
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your Python expertise, data processing experience, and any relevant projects you've worked on. We want to see how you can contribute to our data team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our mission at HENI. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Projects: If you've worked on any cool data projects, make sure to mention them! Whether it's building dashboards or developing data pipelines, we want to know what you've done. Include links to your GitHub or any live demos if possible.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at HENI!
How to prepare for a job interview at HENI
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially Python, SQL, and any cloud tools like AWS or Azure. Be ready to discuss your experience with these technologies and how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in data engineering or software development. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight how you approached problems and what solutions you implemented.
✨Demonstrate Your Analytical Mindset
Since the role involves customer analytics, be prepared to talk about your experience with data analysis and visualisation tools. Bring examples of dashboards or reports you've created, and explain how they impacted decision-making in your previous roles.
✨Ask Insightful Questions
At the end of the interview, ask questions that show your interest in HENI's projects and goals. Inquire about their data initiatives or how they integrate art with technology. This not only shows your enthusiasm but also helps you gauge if the company aligns with your career aspirations.