Azure Data Architect

Ness is a full lifecycle digital engineering firm offering digital advisory through scaled engineering services. Combining our core competence in engineering with the latest in digital strategy and technology, we seamlessly manage Digital Transformation journeys from strategy through execution to help businesses thrive in the digital economy. As your tech partner, we help engineer your company’s future with cloud and data. For more information, visit

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Position Summary

We are seeking a highly skilled Data Architect with deep expertise in Azure, Databricks, SQL, and Data Modeling. The ideal candidate will have extensive experience in both traditional data warehouse architectures and modern data platform paradigms (Data Lake, Lakehouse, and Azure Synapse). This role requires a proven track record in designing and implementing enterprise-scale data solutions, integrating multiple data sources, and enabling analytics at scale.

Key Responsibilities

Lead the architecture, design, and implementation of enterprise data warehouses, data lakes, and Lakehouse's on Azure and Databricks.

Define and enforce data modeling standards, best practices, and guidelines across transactional and analytical workloads.

Architect end-to-end modern data platforms leveraging Azure Synapse, Databricks, Delta Lake, and related Azure services (ADF, ADLS, Purview, etc.).

Solution Delivery

Design scalable ETL / ELT pipelines and orchestrate workflows for ingestion, transformation, and consumption.

Partner with business stakeholders, product teams, and data engineers to deliver high-quality, business-driven data solutions.

Ensure solutions are secure, performant, and compliant with enterprise governance and regulatory standards.

Define data strategy and reference architecture for modernization from legacy / traditional data platforms (Teradata, Oracle, SQL Server, etc.) to modern architectures.

Provide technical leadership and mentoring to engineering teams.

Collaborate with cloud, analytics, and business teams to align data architecture with organizational goals.

Required Skills & Experience

Core Expertise

Proven experience as a Data Architect or Senior Data Engineer / Lead designing and implementing enterprise data warehouses and modern data platforms.

Strong expertise with Databricks : Delta Lake, Lakehouse, Spark (PySpark / Scala), MLflow.

Very strong SQL development and optimization skills.

Strong data modeling (3NF, Dimensional, Data Vault, Canonical Models, etc.).

Complementary Skills

Knowledge of traditional data platforms (Oracle, Teradata, SQL Server, Informatica, etc.) along with modern ELT / ETL frameworks.

Solid understanding of data governance, metadata management, data quality, and security.

Experience in building real-time / streaming data pipelines (Kafka, Event Hub, etc.) is a plus.

Soft Skills

Excellent communication and ability to engage with business SMEs and senior stakeholders.

Strong analytical and problem-solving skills with an enterprise-scale mindset.

Experience in mentoring and guiding teams on modern data practices.

Qualifications

Bachelor’s / master’s degree in computer science, Information Systems, or related field.

15+ years of experience in Data Engineering / Architecture, with at least 5+ years in Azure & Databricks ecosystem.

Proven track record in enterprise-scale data warehouse and Lakehouse implementations.

Certifications in Azure Data Engineer / Architect or Databricks preferred.

Ness is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law

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