Data Engineer

Sisu Group is a fast-growing iGaming startup with over 150 team members and offices in Tallinn and Malaga. We are on a mission to redefine the future of iGaming and sports betting by building cutting-edge technology and next-generation player experiences - In 2024, and were successfully launched. Backed by €21M in secured funding, the majority of our company is owned by the people building it, our team. Sisu promotes a collaborative, non-corporate culture, offering competitive salaries with stock options to match.

We are looking for a Data Engineer to join our Data Team and help build the backbone of our data-driven organisation. In this role, you will design, build, and maintain reliable and cost-efficient data pipelines and models that enable analysts and stakeholders to make better decisions.

About You:

As part of the Data Engineering team, you will partner with data analysts, product teams, developers, and the Data Engineer to create stable, validated, and scalable data foundations. Your work will shift the company from fragile, top-down reporting views to robust, bottom-up data models that serve as the single source of truth.

Your work will shift the company from fragile, top-down reporting views to robust, bottom-up data models that serve as the single source of truth.

The Data Engineer will serve as the key partner to align on data modeling approaches, platform architecture, and standards. You will work closely with the Data Architect to ensure your pipelines and models are designed for long-term scalability, reusability, and alignment across domains.

Must have skills: 

Strong SQL and data modeling experience (fact/dimension design, normalisation/denormalisation)

Proficiency with at least one ETL/ELT framework (Airflow, dbt, etc.)

Hands-on experience with cloud data warehouses (e.g., Redshift, BigQuery, Snowflake)

Solid programming skills (Python, Scala, or similar)

Understanding of data validation, testing, and monitoring

Experience optimising warehouse queries and managing cost efficiency

Bonus points for: 

Familiarity with distributed systems and streaming pipelines (Kafka, Kinesis, Pub/Sub)

Knowledge of CI/CD for data pipelines and infrastructure as code (Terraform)

Exposure to data governance frameworks and metric standardisation

You will be responsible for:

Data Infrastructure & Pipelines:

Design, build, and maintain ETL/ELT pipelines for ingesting data from multiple systems into the warehouse

Ensure high availability, data freshness, and reliability across all pipelines

Implement monitoring, alerting, and logging for pipeline health

Data Modeling & Optimisation: 

Develop and maintain reusable data models for core business domains

Work with data analysts and the Data Architect to translate business needs into stable, validated datasets

Optimise queries and warehouse usage to control costs and improve performance

Establish data validation and testing frameworks to ensure trust in data

Collaboration with Data Analysts & Architect:

Partner with embedded data analysts to understand recurring needs and shift repetitive logic into production-grade models

Provide technical support to analysts (SQL optimisation, schema understanding, data availability)

Collaborate with the Data Architect on design patterns, data contracts, and standards

Create handoffs so analysts can focus on business insights, while engineers ensure data quality and scalability

Governance & Standards:

Contribute to shared data definitions and documentation to ensure consistency across domains

Support the Data Team in promoting best practices for modeling, version control, and deployment

Define and enforce data contracts to prevent unexpected upstream changes from breaking pipelines

Work with the Data Architect to maintain a consistent, organisation-wide data architecture

Tooling & Enablement:

Manage and improve the data platform stack (e.g., Dataform, Airflow, BigQuery, observability tools).

Evaluate and introduce new technologies that improve scalability, performance, or cost efficiency.

Build self-service capabilities that allow analysts and stakeholders to work with data more effectively.

Success in the this role means:

Data analysts spend more time delivering business insights and less time fixing broken models

Core data sets (e.g., user behavior, finance, product usage) are trusted, stable, and cost-efficient

The company moves from fragile, top-down reports to a scalable, bottom-up data foundation

Stakeholders have reliable data to guide roadmaps and strategic decisions

Data engineering practices are aligned with architectural standards set together with the Data Architect

Company culture and benefits:

At Sisu Group we believe in creating a positive and inclusive workplace culture where teamwork is the key. We value collaboration, open communication, and treat all team members as equals. We encourage each other to be proactive and take ownership, while also providing the support and resources needed to help them grow and develop even further.

We understand that our employees are our biggest asset, which is why we offer a competitive compensation package that includes stock options, and generous paid time off. We believe that building a great company is about more than just creating a successful product, it's about building a community of passionate and driven individuals who share a common goal.

If you're looking for a company where you can grow professionally, work with talented and dedicated colleagues, and make a real impact, while sharing our key values of caring, thinking outside the box, taking charge and having a positive mindset, then Sisu Group is the place for you.

By submitting this application, the candidate agrees that Sisu Group stores personal details to be able to process the job application. Sisu Group follows and is compliant with the General Data Protection Regulation. Clear police record required, ensuring a commitment to integrity and a safe workplace.