Databrick Architect

About Persistent

We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what’s next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 18 of the Fortune 50 companies, 7 of the 10 top US banks, 9 of the 10 technology companies, and numerous innovators across the healthcare ecosystem.

Our disruptor’s mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We have delivered 26 sequential quarters of growth with $487.6M in Q4 FY26 revenue, up 7.8% Q-o-Q and 20.0% Y-o-Y.

Our 29,500+ global team members, located in 21 countries, have been instrumental in helping the market leaders transform their industries. We received five awards at the ISG (Information Services Group) Provider Lens™ Awards 2026 and, for the second year in a row, were awarded the Growth Honor of the Year at the Everest Group Elevate 2026.

About Position

We are seeking a highly experienced Databrick Architect to Evaluate and drive adoption of new Databricks capabilities, including Lake base, Databricks Apps, Lakehouse Federation, Serverless, Genie and AI/ML capabilities. Conduct architecture reviews, define reusable patterns and provide technical governance across projects. Partner with business, engineering, and architecture teams to define target-state architectures and modernization roadmaps.

• Role: Databrick Architect
• Location: Tarrytown New York
• Experience: 13+ Years
• Job Type: FTE /Contract

What You'll Do

• Lead enterprise-scale Databricks Lakehouse Architecture design and implementation on AWS.
• Drive large-scale data platform modernisation and cloud transformation initiatives.
• Architect scalable Medallion Architecture (Bronze, Silver, Gold) data platforms.
• Lead migration of legacy EMR, NiFi, Redshift, and ETL workloads to Databricks.
• Design high-performance batch and real-time data processing solutions.
• Build robust ingestion frameworks using Auto Loader, Delta Lake, and Structured Streaming.
• Define enterprise data governance and security standards using Unity Catalog.
• Architect metadata-driven and reusable PySpark-based ETL/ELT frameworks.
• Establish best practices for performance tuning, scalability, and cost optimisation.
• Design and implement data quality, lineage, and observability frameworks.
• Drive adoption of CI/CD, DevOps, Infrastructure as Code, and automation practices.
• Collaborate with business, analytics, and engineering teams to define target-state architectures.
• Conduct architecture reviews and provide technical leadership across multiple projects.
• Mentor architects and senior engineers on Databricks and AWS best practices.
• Design secure and scalable solutions leveraging AWS services (S3, Glue, Athena, Lambda, IAM, Redshift).
• Implement and govern enterprise-wide data access, compliance, and security controls.
• Evaluate and adopt latest Databricks capabilities such as DLT, Lakehouse Federation, Serverless, and MLflow.
• Enable AI/ML, Generative AI, and advanced analytics use cases on the Lakehouse platform.
• Create architecture roadmaps, migration strategies, standards, and governance frameworks.
• Act as the primary technical advisor for customer leadership on data strategy and platform evolution.

Expertise You'll Bring

• Lead enterprise-scale data platform modernization initiatives, driving migration from AWS EMR, Apache NiFi, and legacy ETL frameworks to the Databricks Lakehouse Platform.
• Architect and implement scalable Lakehouse solutions using Databricks, Delta Lake, Unity Catalog, and Databricks Workflows.
• Design and govern end-to-end data pipelines for batch, streaming, CDC, and real-time data integration workloads.
• Provide architecture leadership for large-scale AWS-based data ecosystems leveraging S3, IAM, Redshift, Glue Catalog, Airflow, and Databricks.
• Develop enterprise data architecture standards covering data modelling, metadata management, lineage, governance, security, and compliance.
• Drive adoption of Databricks best practices including Delta Live Tables (DLT), Auto Loader, Unity Catalog, Serverless Compute, Lakehouse Federation, and advanced optimization techniques.
• Lead replatforming and migration programmes involving PySpark applications, Airflow DAGs, EMR workloads, Redshift integrations, and NiFi pipelines.
• Partner closely with business stakeholders, enterprise architects, product owners, and data science teams to define technology roadmaps and target architectures.
• Establish governance frameworks using Unity Catalog, data quality control