At a Glance
- Tasks: Lead the design and implementation of scalable data systems and mentor fellow engineers.
- Company: Join a dynamic team transforming customer engagement with AI-powered technology.
- Benefits: Enjoy 25 days annual leave, enhanced maternity/paternity packages, and personal training allowances.
- Other info: Hybrid working model with a supportive culture focused on learning and innovation.
- Why this job: Make a real impact in a fast-paced tech environment while growing your skills.
- Qualifications: Strong experience in data engineering, SQL, and cloud-native environments required.
The predicted salary is between 60000 - 80000 € per year.
We're the team behind the AI-powered customer engagement platform that's transforming how businesses connect with their customers - turning every conversation into a revenue-driving moment. Our platform helps contact centre teams achieve their goals through intelligent automation, predictive insights, and seamless customer experiences. We build technology that empowers people, not replaces them.
We are proud of our reputation for combining cutting-edge tech with down-to-earth people, we have big ambitions and a clear sense of who we are. Our culture is driven by our values: we take ownership, move fast, challenge the status quo, and learn constantly. Working at MaxContact means being stretched, you’ll be trusted with responsibility early, expected to think commercially, and encouraged to act decisively. We don’t stand still, and neither will you.
At the same time, we believe high performance only works in a safe, supportive environment. You’ll be surrounded by smart, driven people who want to see you succeed, who value openness and honesty, and who see mistakes as part of learning quickly and getting better. We’re builders, problem-solvers, and customer champions who believe in innovation with purpose, human-first technology, and delivering results that matter. You’ll work alongside passionate colleagues building technology that directly impacts how thousands of businesses connect with millions of customers every day. If you’re ambitious, curious, and excited by the idea of building something meaningful in a fast-moving tech business.
The Senior Data Engineer is a technical leader within the data engineering team, responsible for delivering complex, high-impact data pipelines, models, and infrastructure within the technical vision set by the Head of Platform. You will own the design and implementation of reliable and scalable data systems, mentor other engineers, and provide expert input on challenging technical problems. This role is hands‑on while also requiring you to coordinate work across multiple engineers, establish standards, and lead data initiatives. You will work closely with analytics, product, and platform teams to ensure that data solutions are trustworthy, performant, and aligned to business needs, enabling rapid, safe, and informed decision‑making across the organisation.
Responsibilities
- Data Modelling & Warehousing
- Design and maintain dimensional models, semantic layers, and dbt projects for key business domain
- Ensure models are scalable, versioned, and maintain backward compatibility for consumers
- Define and maintain metric definitions in the semantic layer to prevent metric drift
- Build and operate reliable batch and streaming pipelines using tools such as Airflow, dbt, Kafka/Kinesis, or equivalent
- Implement idempotent, replayable ELT/ETL workflows with clear SLAs
- Lead design of complex DAGs including dependencies, backfills, late‑arriving data handling, and data quality checks
- Data Quality & Reliability
- Implement and enforce comprehensive testing frameworks (dbt tests, custom validations, freshness checks)
- Define and manage data contracts between producers and consumers
- Set and monitor SLAs for data freshness and completeness; lead root cause analysis for reliability incidents
- Infrastructure & Platforms
- Work with cloud warehouses/lakehouses (Data Lake, Snowflake, BigQuery, Databricks, or similar)
- Manage and maintain PostgreSQL clusters used for both operational and analytical workloads, ensuring reliability, backups, replication, scaling, and cost optimisation
- Optimise storage formats (Parquet/Delta/Iceberg) for performance and cost efficiency
- Partner with platform engineers on orchestration, data service provisioning, and IAM
- Performance & Cost
- Optimise queries, models, and pipelines for performance, scalability, and cost
- Introduce caching, partitioning, clustering, and materialisation strategies
- Monitor and tune PostgreSQL query performance and indexing strategies
- Collaborate with FinOps and platform to implement cost guardrails and monitoring
- Security & Governance
- Implement RBAC and least‑privilege access controls for datasets and PostgreSQL instances
- Design privacy‑by‑default solutions (masking, tokenisation, row‑level security)
- Contribute to metadata, lineage, and catalogue systems to ensure discoverability and compliance
- Mentor associate and mid‑level data engineers through code reviews, pairing, and structured feedback
- Lead knowledge‑sharing sessions and contribute to internal documentation and training
- Run delivery of multi‑pipeline projects, breaking down epics into slices, sequencing risk and value, and coordinating dependencies
Success Measure
- Pipeline SLAs met consistently; incidents resolved with systemic fixes, not patches
- Comprehensive data quality test coverage across key domains; no recurring issues without RCA and fix
- Measurable improvement in junior engineer capability through active mentoring and code review
- Complex data initiatives delivered on time and to agreed scope
- Positive stakeholder trust scores from analytics, product, and platform teams
- Pipeline and warehouse costs tracked, optimised, and within agreed targets
Values and Behaviours
- Ownership mindset and accountability
- Curiosity and willingness to learn, particularly around AI and emerging technology
- Collaboration over silos
- Adaptable and comfortable in a fast‑moving, scaling business
- Resilience under pressure: calm leadership during incidents and data quality failures, with a focus on systemic improvement
Training and Enablement
- Structured onboarding covering our products, customers, systems, and data landscape
- Full systems and tooling training from day one
- Access to learning resources, conferences, and a professional development budget
- Regular 1:1s with a clear career development conversation about progression into Principal Engineer (IC track) or Engineering Manager (people leadership track)
Skills and Experience
- Strong hands‑on experience delivering complex data engineering projects in cloud‑native environments
- Expert SQL skills and deep knowledge of data modelling (dimensional/star schemas and semantic layers)
- Strong experience with dbt for transformation, testing, and metric definitions
- Proven ability to build and maintain ELT/ETL pipelines (Azure Data Factory, Airflow, Dagster, Prefect, or similar)
- Experience with at least one cloud data warehouse or lakehouse (Snowflake, BigQuery, Databricks, Redshift, or similar)
- Strong PostgreSQL skills including management, tuning, indexing, replication, and performance optimisation
- Solid Python or Scala skills for pipeline development
- Strong knowledge of data testing frameworks, data contracts, and SLAs/SLOs
- Familiarity with streaming data technologies (Kafka, Kinesis, or Pub/Sub)
- Good understanding of storage formats (Parquet, Delta, Iceberg)
- Knowledge of privacy, security, and compliance principles (GDPR, ISO 27001, SOC 2)
- Experience acting as a senior or lead engineer on multi‑person data projects
- Implementing observability and reliability improvements for data systems at scale
- Familiarity with data science workflows and ML feature pipelines
- Experience with FinOps or cost optimisation practices for data infrastructure
- Exposure to data cataloguing, metadata management, or lineage tooling
Benefits and Perks
- 25 days annual leave plus your birthday off
- Increased holiday entitlement with length of service
- Enhanced maternity and paternity packages
- Life insurance
- Enhanced pension options
- Company‑paid sick leave
- Personal training allowance
- Buy and sell holiday options
- Social, charity and culture committee events
- Hybrid working (minimum two days in the office)
- Employee assistant programme
AI in Our Hiring Process: At MaxContact, we expect engineers to work effectively with AI tools every day. We welcome candidates who use AI to prepare their applications and encourage you to demonstrate your ability to collaborate with AI during any take‑home assessments. During live interviews, we will assess your ability to think through problems and make engineering decisions — both with and without AI assistance.
We are an equal opportunity employer, if you require any adjustments during the hiring process please contact.
Senior Data Engineer employer: MaxContact
MaxContact is an exceptional employer that fosters a culture of innovation and collaboration, where employees are empowered to take ownership and drive meaningful change. With a strong commitment to personal growth, we offer extensive training resources, enhanced benefits, and a supportive environment that values openness and learning from mistakes. Located in a dynamic tech hub, our team thrives on the excitement of building impactful technology that transforms customer engagement, making every day at MaxContact both rewarding and fulfilling.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for those interviews! Research the company, understand their tech stack, and be ready to discuss how your skills align with their needs. Practise common interview questions and think of examples that showcase your experience in data engineering.
✨Tip Number 3
Show off your projects! Whether it's a GitHub repo or a personal website, having a portfolio of your work can really set you apart. Highlight any complex data pipelines or innovative solutions you've built – it’s all about demonstrating your hands-on experience.
✨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 being part of our team at MaxContact.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for data engineering shine through! We love seeing candidates who are genuinely excited about building impactful data solutions and driving innovation.
Tailor Your Experience:Make sure to highlight your relevant experience in data modelling, ELT/ETL pipelines, and cloud technologies. We want to see how your skills align with our needs, so don’t be shy about showcasing your achievements!
Be Clear and Concise:Keep your application straightforward and to the point. Use clear language to describe your past projects and responsibilities, as we appreciate candidates who can communicate complex ideas simply.
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!
How to prepare for a job interview at MaxContact
✨Know Your Data Inside Out
Before the interview, dive deep into your past data engineering projects. Be ready to discuss specific challenges you faced, how you overcame them, and the technologies you used. This will show your hands-on experience and technical expertise, which is crucial for a Senior Data Engineer role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss complex data problems you've solved in the past. Think about how you can demonstrate your ability to think commercially and act decisively. Use examples that highlight your ownership mindset and resilience under pressure, as these traits are highly valued.
✨Familiarise Yourself with Their Tech Stack
Research the tools and technologies mentioned in the job description, like dbt, Airflow, and PostgreSQL. If you have experience with similar tools, be ready to explain how you’ve used them effectively. This shows that you’re not only technically proficient but also adaptable to their specific environment.
✨Emphasise Collaboration and Mentorship
Since the role involves mentoring other engineers, prepare to discuss your approach to collaboration and knowledge sharing. Share examples of how you've supported junior team members or led knowledge-sharing sessions. This will demonstrate your leadership potential and commitment to fostering a supportive environment.
