Senior Data Architect

This is a fully remote position, open to applicants in Poland.

📋 Description

• Convert client business goals into scalable, secure, and cost-effective data platform architectures utilizing Databricks.

• Manage the migration of legacy data warehouses, deployment of lakehouse solutions, and enterprise analytics initiatives.

• Design, construct, and implement comprehensive data ingestion pipelines and transformation workflows using Databricks, Apache Spark, Python, SQL, and cloud-native services.

• Aid in defining professional services engagements by creating technical solution designs, architectural blueprints, and estimating efforts.

• Collaborate with delivery teams, client engineers, project managers, enterprise partners, and internal engineering teams.

• Ensure timely and high-quality technical execution.

• Resolve complex implementation issues.

• Produce architectural documentation and establish best practices that promote long-term client self-sufficiency.

• Lead the complete design, implementation, and optimization of scalable data platforms.

• Drive client interactions across data engineering, advanced analytics, and AI projects.

• Migrate legacy systems, deploy production-grade lakehouse architectures, and facilitate technology adoption.

⛳️ Requirements

• Over 8 years of practical experience in data engineering, data architecture, or big data platform development.

• Proficient in Python and SQL.

• Significant expertise in distributed computing and Apache Spark.

• Scala experience is preferred.

• Proven history of building and deploying modern data platforms using Databricks or similar technologies.

• Experience with at least one of the major cloud providers: AWS, Azure, or GCP.

• Understanding of CI/CD automation.

• Knowledge of DevOps best practices for data operations (DataOps).

• Familiarity with managing production-grade pipelines.

• Outstanding consulting abilities.

• Demonstrated capability to lead technical workshops, convey complex concepts to key stakeholders, and guide architectural decisions.

• Hands-on experience with deploying machine learning platforms and production MLOps workflows is preferred.

• Proven success in migrating legacy ETL/data warehouse environments to modern cloud data platforms is preferred.

• Active Databricks certifications are preferred.

• Previous experience in enterprise professional services, technical consulting, or client-facing solutions engineering is preferred.

🏝️ Benefits

• Open to B2B and permanent contract options.

• In-depth exploration of modern Lakehouse architectures (Medallion model, Delta Lake, PySpark).

• Clear opportunities for upskilling in AI/ML engineering.

• Complete location independence throughout Poland.

• Flexible working hours.

• Emphasis on work-life balance.

• Ongoing hands-on experience with emerging Databricks features, multi-cloud platforms (Azure, AWS, GCP), and automated CI/CD data workflows.

• Stability, competitive salary, and long-term project pipelines through a transparent B2B contract structure.