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Job Title: Databricks Data Lake Engineer
Location: New York, NY - Jersey City, NJ

Role Overview:

The Databricks Data Lake Engineer will design, build, and optimize large scale data pipelines across the full lifecycle of data ingestion, migration, curation, and consumption within a modern lakehouse architecture. This role requires hands on expertise with Databricks, Delta Lake, Spark, and cloud-native data platforms, along with the ability to collaborate effectively with business stakeholders, client, architects, and AI/ML teams.

Key Responsibilities:

Data Ingestion - Build scalable ingestion pipelines using Spark, Autoloader, LakeFlow, Informatica, Delta Live Tables, and cloud-native connectors (Kafka, REST, ODBC, CDC - Change Data Capture).
Data Migration - Lead migration of legacy data warehouses, Hadoop clusters, or on prem systems into S3/Delta Lake.
Data Curation - Implement bronze silver gold architecture, enforce quality checks, schema evolution, and governance.
Data Consumption - Deliver curated datasets for BI, analytics, dashboards, and downstream applications.
AI/ML Enablement - Partner with data scientists to prepare feature stores, optimize ML-ready datasets, and support model deployment workflows.
Develop and maintain CI/CD pipelines for Databricks jobs, notebooks, and workflows.
Optimize Spark/SQL/Python jobs for performance, cost efficiency, and reliability.
Implement security, governance, and compliance using Unity Catalog, data lineage, and access controls.
Collaborate with cross-functional teams and communicate technical concepts clearly to non-technical stakeholders.

Required Skills & Experience:

16 years of education with minimum 5+ years of hands-on experience in data engineering with cloud platforms (AWS preferred).
Strong expertise in Databricks, Delta Lake, Apache Spark, and distributed data processing.
Experience with Python, SQL, and ETL/ELT frameworks.
Proven experience with data migration from legacy systems to cloud data lakes.
Deep understanding of data modeling, curation layers, and consumption patterns.
Familiarity with ML workflows, feature engineering, and model operationalization.
Experience with DevOps, Git, CI/CD, and job orchestration tools.
Excellent communication skills with the ability to translate complex concepts into clear business language.

Preferred Qualifications:

Experience with AWS Databricks, Azure Data Factory Glue, Airflow, Kafka, Informatica, or similar ingestion tools.
Knowledge of Unity Catalog, Delta Sharing, and enterprise governance frameworks.
Exposure to AI/ML platforms, MLOps, or Databricks Feature Store.
Certifications: Databricks Data Engineer Associate/Professional, AWS and Azure Data Engineer.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10106248
Position Id: 2026-4299
Posted 9 hours ago

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