N-iX is a global software engineering and technology services company, building solutions for clients since 2002. Our teams work across Europe, the Americas, and Asia for Fortune 500 companies and fast-growing businesses in finance, retail, manufacturing, telecom, healthcare, and more. Our Data & Analytics practice designs and delivers modern data platforms on Snowflake, Databricks, Azure and AWS, from first assessment to production at scale.
We are looking for a Data Architect to lead the design of cloud data platforms for our clients. You will own the target architecture end-to-end, work directly with client stakeholders, and guide engineering teams through delivery. The role mixes hands-on technical leadership with consulting: you will shape solutions in pre-sales, run discovery workshops, and stay accountable for architecture quality once the project is live.
Responsibilities:
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Design end-to-end data architectures on Snowflake and/or Databricks, deployed on Azure and/or AWS: ingestion, storage, processing, serving and consumption layers.
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Define lakehouse and data warehouse patterns (medallion architecture, data vault, dimensional models) and choose the right one for each use case.
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Lead migrations from legacy platforms (on-prem DWH, Hadoop, Teradata, Oracle, SQL Server) to the cloud, including assessment, roadmap and cutover plan.
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Set standards for data modelling, pipeline design, CI/CD, infrastructure as code and environment strategy.
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Design data governance, security and compliance: access control, data lineage, cataloguing (Unity Catalog, Snowflake Horizon, Purview), GDPR and local LATAM privacy laws.
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Optimize platform cost and performance (warehouse sizing, cluster policies, FinOps practices).
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Run discovery workshops and architecture reviews with client business and technical stakeholders, in English.
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Support pre-sales: solution design, effort estimates, technical sections of proposals and client presentations.
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Mentor data engineers and review their designs and code; act as the technical point of escalation on the project.
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Prepare data foundations for BI, advanced analytics, ML and GenAI use cases.
Requirements:
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8+ years in data engineering or data platforms, including 3+ years as a Data or Solution Architect.
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Hands-on production experience with Snowflake and/or Databricks (at least one in depth).
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Strong knowledge of Azure and/or AWS data services, for example:
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Azure: ADLS Gen2, Data Factory, Synapse/Fabric, Event Hubs, Purview, Key Vault
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AWS: S3, Glue, Redshift, Kinesis, Lambda, Lake Formation, IAM
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Expert SQL and solid Python or Scala; experience with Spark.
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Proven experience with data modelling (dimensional, data vault) and lakehouse design.
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Experience with orchestration and transformation tools such as Airflow, dbt, Azure Data Factory or Databricks Workflows.
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Working knowledge of infrastructure as code (Terraform, Bicep or CloudFormation) and CI/CD for data.
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Track record of leading at least one cloud data platform build or migration from design to production.
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Client-facing consulting experience: running workshops, presenting architecture decisions, managing expectations.
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At least B2 English, written and spoken.
Nice to have:
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Certifications: SnowPro Advanced Architect, Databricks Certified Data Engineer Professional, Azure Solutions Architect Expert, AWS Solutions Architect Professional or AWS Data Analytics/Data Engineer.
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Streaming architectures (Kafka, Spark Structured Streaming, Snowpipe Streaming, Delta Live Tables).
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Data mesh, data products and data contracts in practice.
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MLOps and GenAI data foundations (feature stores, vector search, RAG pipelines).
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Domain experience in banking, insurance, retail, telecom or energy.
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