Data Architect

Job Description

Databricks Champion -Data Architect

Role Overview

We are looking for an experienced Data Architect – Databricks Champion recognition to provide architecture and technical leadership for enterprise-scale data platforms built on Azure Databricks and Lakehouse architecture. Need to have.

The candidate should combine strong architectural expertise with hands-on data engineering experience and be capable of translating complex business requirements into scalable, secure, governed and high-performance data solutions. The role will work closely with Data Architects, Data Engineers, Analytics teams and business stakeholders while mentoring engineering teams and establishing Databricks architecture and development best practices.

Key Responsibilities

• Architect and lead enterprise-scale Azure Databricks Lakehouse solutions.
• Design scalable Bronze, Silver and Gold architectures for ingestion, transformation, integration and data consumption.
• Lead complex ETL/ELT, data migration and modernization initiatives across multiple source systems and business domains.
• Define reusable architecture patterns, engineering standards and frameworks using Databricks, Spark, PySpark, SQL and Delta Lake.
• Design and review analytical and dimensional data models, including Fact/Dimension and Star Schema models.
• Drive performance optimization of Spark workloads, SQL queries and data pipelines.
• Establish standards for data quality, governance, metadata, lineage, security, monitoring and access management.
• Define engineering practices around Git, CI/CD, automated deployment and code quality.
• Conduct architecture/design reviews and provide hands-on technical guidance to Data Engineers.
• Mentor engineering teams and collaborate with senior business and technical stakeholders on solution design, technical dependencies and risks.

Technical Skills & Certifications - Essential Skills

• 10–15 years of experience in Data Engineering/Data Architecture.
• Strong hands-on expertise in Azure Databricks and Lakehouse architecture.
• Advanced skills in Apache Spark, PySpark, Python, SQL and Delta Lake.
• Strong understanding of Bronze/Silver/Gold architecture and enterprise ETL/ELT patterns.
• Experience with batch/incremental processing, schema evolution and large-scale data pipelines.
• Experience with AI/ML, Generative AI, and Databricks Mosaic AI.
• Strong knowledge of dimensional modelling, Fact/Dimension modelling and Star Schema.
• Experience with data governance, data quality, metadata, lineage, security and access management.
• Strong working knowledge of Git, CI/CD and DevOps practices.
• Experience in data-platform modernization and migration.
• Strong architecture, problem-solving, stakeholder-management and technical-leadership skills.

Certifications / Databricks Recognition

• Databricks Champion recognition
• Databricks Certified Data Engineer Professional.
• Databricks AI certifications.
• Azure Platform Architect accreditation or equivalent Databricks architecture credentials would be an advantage.
• Demonstrated experience architecting and delivering enterprise-grade Databricks solutions is essential.

Qualifications

Additional Information

At Tieto, we believe in the power of diversity, equity, and inclusion. We encourage applicants of all backgrounds, genders (m/f/d), and walks of life to join our team, as we believe that this fosters an inspiring workplace and fuels innovation. Our commitment to openness, trust, and diversity is at the heart of our mission to create digital futures that benefit businesses, societies, and humanity.
Diversity, equity and inclusion | Sustainability | Tieto

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