Lead Databricks Data Engineer
Location: New York, NY – Hybrid (3 Days Onsite/Week)
Experience: 6+ Years
Employment Type: Full Time
Job Description
We are looking for an experienced Lead Databricks Data Engineer to design, develop, and optimize scalable data engineering solutions. The ideal candidate must have strong hands-on experience with Databricks, PySpark, Delta Lake, Snowflake, and modern cloud data platforms.
Minimum 2+ years of genuine, hands-on Databricks experience within the last 2 years is mandatory. Candidates must be able to demonstrate recent project experience and strong technical expertise.
Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, Python, and SQL.
Build and optimize data pipelines using Delta Lake and Medallion Architecture (Bronze, Silver, Gold).
Develop and maintain data engineering frameworks and reusable components.
Integrate Databricks with Snowflake and cloud-based data platforms.
Implement data orchestration using Apache Airflow and Databricks Workflows.
Optimize Spark jobs, SQL queries, cluster performance, and data processing costs.
Implement data quality, governance, monitoring, and observability practices.
Collaborate with architects, business stakeholders, and engineering teams to define technical solutions.
Provide technical leadership, code reviews, architecture guidance, and mentorship to data engineering teams.
Required Skills
6+ years of experience in Data Engineering.
2+ years of recent, hands-on Databricks experience within the last 2 years (Mandatory).
Strong experience with Azure Databricks or Databricks on AWS.
Strong programming skills in Python, PySpark, and SQL.
Hands-on experience with Delta Lake and Medallion Architecture.
Strong knowledge of Apache Spark and performance optimization.
Experience with Snowflake and data warehousing concepts.
Experience with Apache Airflow or similar orchestration tools.
Knowledge of cloud platforms (Azure, AWS, or Google Cloud Platform).
Experience in technical leadership, architecture, and mentoring.
Preferred Qualifications
Experience with Unity Catalog, Delta Live Tables, and Databricks Workflows.
Knowledge of streaming technologies such as Kafka.
Experience with CI/CD, DataOps, and Infrastructure as Code.
Exposure to data governance, security, and data quality frameworks.
Experience in enterprise-scale data modernization projects.
Important Requirement
Candidates must have genuine recent hands-on Databricks development experience. Profiles with only theoretical knowledge, limited migration exposure, or primarily Microsoft Fabric/Snowflake experience without recent Databricks implementation will not be considered.
Interested candidates can share their updated resume along with current location, work authorization, and availability.