Databricks Engineer

Remote

Only W2 No Corp to Corp

Open to Sponsorship

NO OPT'S PLEASE

MUST BE A 'DATABRICKS " SME

• Sr.Data engineering experience, with hands-on data pipeline design and development experience with Databricks, including specific -platform features like Delta Lake, Uniform (Iceberg), Delta Live Tables (Lakeflow Declarative pipelines), and Unity Catalog.
• Proficiency in designing and building robust, scalable, YAML configuration driven data pipelines with batch, micro-batch, and streaming data ingestion and processing patterns using tools like Auto Loader demonstrating a strong understanding of modern data engineering practices.Experienced in building complex job/workflow orchestration patterns using either Databricks jobs/workflows or with other orchestration tools like Airflow, dbt etc.
• Exposure in building robust data quality, pipeline audit/observability solutions with Databricks native features and/or other data quality tools/frameworks like Great Expectations, Collibra, dbt etc.
• Proficiency in Big Data Platforms: Apache Spark, Presto, Amazon EMR
• Experience with Cloud Data Warehouses: Amazon Redshift, Snowflake, Google BigQuery.
• Strong programming skills using SQL, Stored Procedures and Object-Oriented Programming languages (like Java, Python, PySpark etc.).
• Familiarity with building DevOPs, CI/CD pipelines using Databricks Asset Bundles with automated validation and testing.
• Exposure with Infrastructure as Code (IaC) tools like Terraform is a big plus.
• Familiarity with NoSQL Databases and Container Management Systems.
• Experience with agentic AI tooling and frameworks and applying autonomous or semi-autonomous agents within data engineering, orchestration, analytics, or platform automation use cases.
• Hands-on experience leveraging AI-powered coding assistants such as GitHub Copilot, Codex Claude Code, Cursor, Windsurf or similar tools to accelerate development, improve test coverage, enhance documentation, and drive engineering productivity in enterprise environments.
• Interest in exploring AI-native development patterns and embedding intelligent automation into modern Lakehouse and cloud-native data architectures.
• An ideal candidate will have Databricks Data Engineering Associate and/or Professional certification completed with multiple Databricks project delivery experiences.