Data and AI Engineer (f/m/x)
Sii
This is a senior role combining data engineering and artificial intelligence, focused on building cloud-native data and AI solutions on AWS. You will design scalable architectures for batch and real-time data processing, implement end-to-end data pipelines, productionize machine learning workflows, and configure intelligent agents for automation. The position is within Sii, an IT outsourcing company, meaning you will likely work on client projects in a hybrid model from Warsaw. Despite the AI component, the core is data engineering with machine learning deployment.
Brak jawnych widełek — wynagrodzenie do ustalenia podczas rekrutacji.
Brakuje: salary range, specific aws services and ml frameworks used.
This is a senior role combining data engineering and artificial intelligence, focused on building cloud-native data and AI solutions on AWS. You will design scalable architectures for batch and real-time data processing, implement end-to-end data pipelines, productionize machine learning workflows, and configure intelligent agents for automation. The position is within Sii, an IT outsourcing company, meaning you will likely work on client projects in a hybrid model from Warsaw. Despite the AI component, the core is data engineering with machine learning deployment.
- ✓B2B contract allowing for flexible tax optimization
- ✓Modern cloud-native stack focused on AWS
- ✓Senior role with autonomy in designing and implementing solutions
- ✓Opportunity to work on both data engineering and AI/ML projects
- −No salary range provided in the offer, which may indicate below-market compensation
- −The role is through an outsourcing company (Sii), meaning you may be assigned to different client projects with less ownership and stability
- −Vague mention of 'intelligent agents' without clear definition or tools – may be buzzword-heavy
- !No details on specific AWS services or ML frameworks used (e.g., SageMaker vs custom deployment)
- !The combination of data engineering and AI may imply a wide range of responsibilities, risking lack of focus
- !No information about team size or who you report to
- ?Brak jawnych widełek — wynagrodzenie do ustalenia podczas rekrutacji
- •Designing scalable architectures for batch, event-driven, and near-real-time data processing on AWS
- •Building end-to-end data ingestion, processing, storage, and monitoring pipelines using services like AWS Glue, Lambda, Redshift, and S3
- •Productionizing machine learning workflows, including feature engineering, model training, and deployment
- •Configuring and integrating intelligent agents and reusable components for data quality, reporting, and automation
- •Developing APIs and services to expose data and AI products to other systems
- •Implementing CI/CD pipelines, automated testing, and infrastructure as code for data platforms
- •Collaborating with cross-functional teams to translate business requirements into technical solutions
- •Maintaining clear technical documentation and code quality standards
Oferta dla doświadczonych specjalistów (Senior).
A data engineer with at least 5 years of experience, strong in Python and SQL, with hands-on experience building data pipelines on AWS (e.g., S3, Redshift, Glue) and some exposure to deploying ML models. You can work independently but also communicate effectively in English.
Juniors or those with less than 5 years of data engineering experience. Also not suitable for candidates seeking fully remote work or who prefer product-based companies over outsourcing.
- ?Which specific AWS services are used in the current projects? (e.g., Glue, Lambda, SageMaker, Kinesis)
- ?What ML frameworks or tools do you typically use for model deployment? (e.g., TensorFlow, PyTorch, MLflow)
- ?What does 'intelligent agents' mean in this context? Are we talking about AWS Bedrock agents, LangChain, or custom solutions?
- ?How many days per week are expected in the Warsaw office?
- ?What is the typical team size and composition (data engineers, ML engineers, etc.)?
- ?Will I be working on a single client project or rotating between projects?
- ?Are there on-call duties or support responsibilities for production systems?
- −Salary range
- −Specific AWS services and ML frameworks used
- −Team size and reporting structure
- −Client industry or domain of projects
- −Benefits package (e.g., equipment, training budget)