Are you a Principal Engineer or Architect who excels at translating complex client goals into robust, production-ready lakehouse architectures?
Excited to bridge the gap between deep technical execution (Spark, Python, DataOps) and executive-level consulting across multi-cloud environments?
So please, take a few minutes and read about your potential new job.
Our client is an innovative AI and data solutions consultancy and we are seeking a motivated Senior Data Architect.
In this customer-facing role, you will lead the end-to-end design, implementation, and optimization of scalable data platforms built on Databricks and modern cloud ecosystems.
As a technical authority, you will drive high-impact client engagements across data engineering, advanced analytics, and AI initiatives. You will partner directly with client stakeholders, enterprise partners, and internal engineering teams to migrate legacy systems, deploy production-grade lakehouse architectures, and ensure seamless technology adoption.
This is a 100% fully remote role with Poland and it is available on a B2B contract only.
Your tasks will include
- Translate client business objectives into scalable, secure, and cost-optimized data platform architectures powered by Databricks.
- Oversee complex implementations, including legacy data warehouse migrations, lakehouse deployments, and enterprise analytics solutions.
- Design, build, and productionize robust end-to-end data ingestion pipelines and transformation workflows using Databricks, Apache Spark, Python, SQL, and cloud-native services.
- Assist in scoping professional services engagements by delivering technical solution designs, architectural blueprints, and accurate effort estimations.
- Partner with the delivery teams, client engineers, and project managers to drive on-time, high-quality technical execution.
- Troubleshoot complex implementation challenges, author architectural documentation, and establish best practices to support long-term client self-sufficiency.
To be a good fit for the Senior Data Architect you will have
- 8+ years of hands-on experience in data engineering, data architecture, or big data platform development.
- Proficient in Python and SQL; strong expertise in distributed computing and Apache Spark (Scala experience preferred).
- Proven track record building and deploying modern data platforms using Databricks (or comparable technologies) alongside at least one major cloud provider (AWS, Azure, or GCP).
- Familiarity with CI/CD automation, DevOps best practices for data operations (DataOps), and production-grade pipeline management.
- Exceptional consulting skills with demonstrated ability to lead technical workshops, communicate complex concepts to key stakeholders, and steer architectural decisions.
Preferred Qualifications
- Hands-on experience deploying machine learning platforms and production MLOps workflows.
- Demonstrated success migrating legacy ETL/data warehouse environments to modern cloud data platforms.
- Active Databricks certifications (e.g., Databricks Certified Professional Data Engineer).
- Previous experience in enterprise professional services, technical consulting, or client-facing solutions engineering.
Reasons to join
- Deep-dive into modern Lakehouse architectures (Medallion model, Delta Lake, PySpark) with a team that specializes exclusively in high-performance cloud data and AI platforms.
- Beyond core ETL, your work directly powers enterprise AI, MLOps, and Generative AI initiatives—offering a clear path to upskill in AI/ML engineering.
- Enjoy total location independence anywhere in Poland with flexible working hours designed around trust, outcomes, and work-life balance.
- Solve complex data engineering challenges for top-tier enterprise clients across finance, healthcare, and tech without the corporate red tape.
- Gain continuous hands-on experience with emerging Databricks features, multi-cloud platforms (