Position :: Databricks Data Architect
Location :: 100% Remote
Duration :: 12+ months
Interview :: Video
Job Description:
It’s more of a hands-on architect who has 3+ years with Databricks and can still speak to being hands on with Pyspark, Python, SQL etc.
Notes:
Remote
In an Azure infrastructure implementation
Databricks data engineering experience and we are now looking and evaluating -we think it’s a great solution and slowly migrate SQL server systems into databricks
Job Description:
Position Summary
This role is ideal for someone who enjoys building well-architected data solutions, thrives in a modern cloud analytics environment, and wants to influence a next-generation Lakehouse platform. The engineer will play a central role in shaping data quality, architecture, and analytic capabilities across multiple domains.
We are seeking a skilled Databricks Data Engineer to help build and optimize a modern data platform leveraging the Databricks Lakehouse architecture. This role focuses on designing reliable ETL/ELT pipelines, implementing data governance within Unity Catalog, and enabling high-quality analytics products for internal and client-facing use.
Key Responsibilities
o Design and develop data pipelines using Databricks (Python, SQL, Delta Live Tables, Workflows) to ingest, transform, and curate data across bronze, silver, and gold layers.
o Implement and enforce governance standards within Unity Catalog, including catalog/schema/volume organization, permissions, lineage, and metadata management.
o Build and optimize Delta Lake tables, including performance tuning, schema evolution strategies, audit patterns, and CDC approaches (e.g., Change Tracking, timestamp deltas).
o Collaborate closely with architects and data teams to translate business requirements into scalable data models and operational pipelines.
o Develop reusable frameworks and best practices for ingestion, orchestration, DevOps, monitoring, and quality validation.
o Support CI/CD workflows for Databricks assets via Git-based development and automated deployment pipelines.
o Ensure reliability and observability, including logging, testing, and performance diagnostics across the platform.
o Contribute to cloud architecture decisions, such as storage design, identity management, and compute strategies (jobs, clusters, SQL warehouses).
Required Skills & Experience
o 3+ years of experience in data engineering, preferably in a cloud environment (Azure, AWS, or Google Cloud Platform).
o Hands-on experience with Databricks (Delta Lake, Workflows, DLT, Unity Catalog).
o Strong proficiency in SQL and Python for data transformation and pipeline development.
o Solid understanding of ETL/ELT patterns, medallion architecture, data modeling, and schema design.
o Experience with CI/CD using Git-based workflows.
o Working knowledge of cloud storage technologies (ADLS, S3, S).
o Familiarity with table-level governance, permissions, and security models in modern data platforms.
Preferred Qualifications
o Experience integrating SQL Server Change Tracking, timestamp-based incremental ingestion, or similar CDC patterns.
o Exposure to Terraform or IaC for Databricks governance and infrastructure configuration.
o Understanding of analytics ecosystems such as Power BI, Tableau, or Business Objects.
o Background working with domain-driven data models (e.g., CEDS, education data, ERP/operational domains).
o Experience building multi-tenant data products or securely partitioned data architectures.
Soft Skills
o Strong problem-solving mindset and ability to work in fast-moving, collaborative environments.
o Clear, proactive communication that supports cross-team alignment.
o A commitment to documentation, quality, and repeatable processes.
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