[Hiring] Databricks Architect @Cogniify

Role Description

We're seeking a Databricks Architect (Senior/Specialist level) to serve as a senior technical authority for data architecture and analytics engineering on the Databricks Lakehouse platform across Cognify Analytics and our client engagements. In this role, you will design and own Databricks-based data platform architecture, lead complex data engineering initiatives, and ensure our data capabilities are enterprise-grade, governed, and future-ready. You will bridge data engineering, analytics, and AI/ML — combining deep hands-on expertise in Databricks, Python, and SQL with strong architectural judgment and stakeholder communication.

Qualifications

• Bachelor's, Master's, or equivalent professional experience in Computer Science, Data Science, Statistics, or a related field.
• 6–9 years of professional experience in data engineering, analytics engineering, or data architecture, with demonstrated technical leadership on at least a few large-scale engagements.
• Mandatory, hands-on expertise in Databricks, Python, and SQL in production environments.
• Strong working knowledge of the modern data stack: dbt, Airflow/Dagster, Fivetran/Airbyte, Spark, Kafka, and cloud-native data services.
• Solid grasp of data modeling methodologies (Kimball, Data Vault, Activity Schema, OBT) and the judgment to apply them across contexts.
• Experience with cloud data infrastructure on AWS, Azure, or GCP (any combination is acceptable, alongside Databricks).
• Proven ability to influence technical direction and align technical and business stakeholders on complex architecture topics.
• Strong understanding of data governance, data quality, cataloging, lineage, and regulatory compliance frameworks.
• Experience mentoring engineers and contributing to a high-performing data team.
• Strong understanding of how data platforms serve AI/ML workloads, including feature engineering, vector data, and model input/output pipelines.

Requirements

• Own the architecture and design of Databricks-based data platforms, including lakehouse design (Delta Lake), medallion architecture, and unified analytics layers.
• Serve as the senior technical authority on Databricks platform design, providing guidance on architecture, tooling, modeling, and engineering standards across teams and projects.
• Design and build ingestion, transformation, and orchestration pipelines using Python, SQL, PySpark, and Databricks Workflows.
• Architect data mesh and data product strategies, defining domain ownership, data contracts, and self-service consumption patterns on Databricks.
• Establish and evangelize best practices across the data lifecycle: ingestion, transformation, modeling, quality, observability, governance, and consumption.
• Drive the integration of Databricks with AI/ML capabilities, including feature engineering pipelines, vector data infrastructure for RAG, and MLflow-based model workflows.
• Lead complex data migration, platform modernization, and consolidation initiatives for enterprise clients across industries.
• Evaluate emerging data technologies (Apache Iceberg, Unity Catalog, Delta Live Tables, Mosaic AI) to inform architectural decisions.
• Solve complex, ambiguous, high-impact data architecture problems that span multiple teams, platforms, or organizational boundaries.
• Drive cross-functional alignment between data engineering, analytics, AI/ML, platform engineering, security, and product teams.
• Mentor senior data engineers and analysts, fostering a culture of technical excellence.
• Represent Cognify Analytics in discussions with client stakeholders and leadership on data capabilities, strategy, and technical roadmaps.
• Define and enforce data governance, compliance (GDPR, HIPAA, SOC2), and responsible data management standards across all Databricks environments.
• Drive FinOps maturity for the Databricks platform, including compute optimization, cluster policies, storage lifecycle management, and cost forecasting.

Benefits

• Unlimited PTO
• Generous parental leave, above industry standards
• Open communication with management and company leadership
• Small, dynamic teams = massive impact
• Medical, Dental, and Vision coverage
• Access to Disability & Life insurance
• Mental health and wellbeing support
• Annual bonus program
• Employer Stock Purchase Program (ESPP)
• Yearly team building experiences
• Mentorship and sponsorship opportunities
• Manager resources and support