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Data Platform Engineer (5/840) @ - małopolskie - Infolet sp. z o.o.
Opis
Must have8+ years of experience in data engineering, including at least 2 years building lakehouse architectures
Proven experience delivering production-grade data platforms in cloud environments
Strong hands-on expertise with AWS (S3/Blob storage, RDS/SQL DB, managed Kafka, serverless compute)
Expert-level SQL and deep understanding of data modeling (dimensional, SCD2, normalization/denormalization)
Proficiency with Python or Scala for data processing and automation
Experience with stream processing (Kafka, Flink, Spark Streaming, Kinesis)
Hands-on experience with DBT, Databricks SQL, Dataform, or similar transformation frameworks
Strong orchestration skills using Airflow, Prefect, Dagster, or equivalent
Solid understanding of IaC (Terraform, CloudFormation, Pulumi)
Ability to explain technical trade-offs (cost, performance, complexity) to non-technical stakeholders
Strong problem-solving skills: debugging data quality issues, optimizing queries, resolving schema conflicts
Fluent English (business and technical communication)
Nice to have
Experience with search technologies (OpenSearch, Elasticsearch, Solr)
Advanced graph skills:
Cypher, SPARQL, Gremlin, or graph ETL pipelines
Familiarity with data quality frameworks (Great Expectations, dbt tests)
Experience with real-time event processing (Flink, Spark Streaming, Lambda-based pipelines)
Knowledge of observability tools (Grafana, Datadog, CloudWatch)
Background in data governance, reporting platforms, or enterprise analytics
Experience working in regulated or security-focused environments
,(Design and implement a cloud-based data lakehouse platform ingesting engineering and security telemetry from multiple sources, Build scalable Bronze/Silver/Gold data layers, ensuring reliable ingestion, transformation, and consumption patterns, Develop and maintain streaming and batch pipelines using technologies such as Kafka, Flink, Spark Streaming, or Kinesis, Model complex relationships using graph databases (Neo4j, Neptune, TigerGraph) to support advanced analytics and AI-driven use cases, Collaborate with data scientists, platform engineers, and security teams to deliver high‑quality, production-grade data solutions, Implement robust data transformation frameworks (dbt, Databricks SQL, Dataform, or custom SQL/Python pipelines), Build and maintain orchestration workflows using Airflow, Prefect, Dagster, Step Functions, or similar tools, Define and enforce data modeling standards, including dimensional modeling, SCD2, and normalization strategies, Use Infrastructure as Code (Terraform, CloudFormation, Pulumi) to provision and manage cloud resources, Ensure observability and reliability of pipelines through monitoring, alerting, and data quality validation, Work autonomously in a fast‑moving environment, proposing solutions even when requirements are incomplete)
Requirements:
SQL, AWS, dbt, Databricks, Dataform, IaC,
Airflow Additionally:
Sport subscription, Private healthcare, International projects, Life & group insurance, Free coffee, Bike parking, No dress code.
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