Data Architect (Databricks)

Job Description

Job Description

Allata is a global consulting and technology services firm with offices in the US, India, and Argentina. We help organizations accelerate growth, drive innovation, and solve complex challenges by combining strategy, design, and advanced technology. Our expertise covers defining business vision, optimizing processes, and creating engaging digital experiences. We architect and modernize secure, scalable solutions using cloud platforms and top engineering practices.

Allata also empowers clients to unlock data value through analytics and visualization and leverages artificial intelligence to automate processes and enhance decision-making. Our agile, cross-functional teams work closely with clients, either integrating with their teams or providing independent guidance—to deliver measurable results and build lasting partnerships.

We are looking for a Databricks Architect with strong experience in enterprise data platform architecture and governance to lead client-facing data platform implementations. This role blends high-impact architectural responsibilities (reference architectures, security, scalability, cost management, operational model) with technical leadership in designing, building, deploying, and optimizing data pipelines and data products on Lakehouse / EDW platforms (with an emphasis on Databricks). You will own the full lifecycle of data products and standardize patterns, tools, and practices across large-scale, vertical-specific implementations for our clients.

Role & Responsibilities :

• Define the overall data platform architecture (Lakehouse / EDW), including reference patterns (Medallion, Lambda, Kappa), technology selection, and integration blueprint.
• Design conceptual, logical, and physical data models to support multi-tenant and vertical-specific data products; standardize logical layers (ingest / raw, staged / curated, serving).
• Establish data governance, metadata, cataloging (e.g., Unity Catalog), lineage, data contracts, and classification practices to support analytics and ML use cases.
• Define security and compliance controls : access management (RBAC / IAM), data masking, encryption (in transit / at rest), network segmentation, and audit policies.
• Architect scalability, high availability, disaster recovery (RPO / RTO), and capacity & cost management strategies for cloud and hybrid deployments.
• Lead selection and integration of platform components (Databricks, Delta Lake, Delta Live Tables, Fivetran, Azure Data Factory / Data Fabric, orchestration, monitoring / observability).
• Design and enforce CI / CD patterns for data artifacts (notebooks, packages, infra-as-code), including testing, automated deployments and rollback strategies.
• Define ingestion patterns (batch & streaming), file compacting / compaction strategies, partitioning schemes, and storage layout to optimize IO and costs.
• Specify observability practices : metrics, SLAs, health dashboards, structured logging, tracing, and alerting for pipelines and jobs.
• Act as technical authority and mentor for Data Engineering teams; perform architecture and code reviews for critical components.
• Collaborate with stakeholders (Data Product Owners, Security, Infrastructure, BI, ML) to translate business requirements into technical solutions and roadmap.
• Design, develop, test, and deploy processing modules using Spark (PySpark / Scala), Spark SQL, and database stored procedures where applicable.
• Build and optimize data pipelines on Databricks and complementary engines (SQL Server, Azure SQL, AWS RDS / Aurora, PostgreSQL, Oracle).
• Implement DevOps practices : infra-as-code, CI / CD pipelines (ingestion, transformation, tests, deployment), automated testing and version control.
• Troubleshoot and resolve complex data quality, performance, and availability issues; recommend and implement continuous improvements.

Hard Skills - Must have :

Hard Skills - Nice to have / It's a plus :

Soft Skills / Business Specific Skills :

At Allata, we value differences.

Allata is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Allata makes employment decisions without regard to race, color, creed, religion, age, ancestry, national origin, veteran status, sex, sexual orientation, gender, gender identity, gender expression, marital status, disability or any other legally protected category.

This policy applies to all terms and conditions of employment, including but not limited to, recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.