Senior Data Architect, Snowflake, Databricks

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

📋 Description

• Provide guidance to business and technology leaders through discovery workshops, priority clarification, and architectural analysis of options.

• Develop enterprise data architectures by evaluating legacy systems and designing warehouse or lakehouse platforms, integration patterns, migration phases, and target operational setups.

• Oversee data migration and integration processes, including ETL/ELT, batch and incremental data ingestion, change data capture, orchestration, reconciliation, testing, and production cutover.

• Analyze and troubleshoot SQL, pipelines, data models, and integrations, focusing on reliability, performance, and cost-efficiency.

• Create data layers using data modeling and medallion Bronze/Silver/Gold patterns, incorporating data quality, lineage, security, and lifecycle management controls.

• Design governed data sharing solutions between organizations and evaluate private exchanges, marketplace offerings, and commercially viable data products.

• Manage roadmaps, dependencies, architectural decisions, and stakeholder communications while documenting risks and trade-offs.

• Share knowledge, mentor delivery teams, and identify additional consulting opportunities in platform engineering, governance, analytics, and AI.

• Provide architecture decisions, migration roadmaps, reliable production data platforms, governed pipelines, data models, and sharing solutions for clients.

⛳️ Requirements

• Extensive hands-on experience in designing, implementing, or migrating production enterprise workloads on at least one of Snowflake or Databricks.

• Proficiency in Snowflake platform architecture, data loading and ELT processes, warehouse performance and cost management, security, and features such as Snowpipe, Streams, Tasks, Dynamic Tables, secure sharing, or Marketplace listings.

• Expertise in Databricks lakehouse architecture, Delta Lake, Spark/PySpark or Databricks SQL, Unity Catalog, and ingestion/orchestration capabilities like Lakeflow, Auto Loader, Delta Sharing, or Marketplace.

• Demonstrated experience in enterprise data migration and engineering across complex data sources, including source-to-target mapping, ETL/ELT, pipeline orchestration, data quality management, reconciliation, and controlled production transitions.

• Strong SQL skills across relational databases such as SQL Server, Oracle, or PostgreSQL.

• Familiarity with dimensional and layered/medallion data models, query optimization, and transformation logic.

• Practical knowledge of access control, lineage, auditability, sensitive data handling, governed sharing, and reusable data products.

• Capability to lead workshops, constructively challenge assumptions, and present technical strategies and delivery recommendations to business executives and engineering leaders.

• Proven track record of managing significant data initiatives through the phases of discovery, architecture, planning, and implementation, including managing dependencies, milestones, and stakeholder expectations.

• Experience with both Snowflake and Databricks is a plus.

• Migration experience with AWS, Microsoft Azure, or Google Cloud would be advantageous.

• Relevant cloud certifications would be beneficial.

• Familiarity with Power BI, Tableau, Python, dbt, Airflow, or similar orchestration tools would be an asset.

• Relevant certifications such as SnowPro, Databricks, AWS, Azure, or other cloud/data credentials would be advantageous.

• A structured, credible, and pragmatic consulting approach.

• Effective communication skills with senior stakeholders and engineering teams.

• English communication skills will be assessed during the application process.

🏝️ Benefits

• Long-term role involving multiple client engagements.

• Opportunities for professional growth through knowledge transfer and mentoring.

• Exposure to consulting engagements with Snowflake and Databricks.

• Opportunities to work within the insurance, healthcare, and retail industries.

• Opportunities to engage in analytics, AI, and data product development.