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Databricks Data Lake Engineer

AIT Global, Inc.Jersey City, NJ🇺🇸United StatesPosted 22 Jul 2026

Why This Role Stands Out

This hybrid Databricks Data Lake Engineer role offers a fantastic opportunity to shape and optimize large-scale data pipelines within an innovative lakehouse architecture, providing significant growth potential and impactful work. If you excel in Databricks, Delta Lake, and Spark, and thrive in collaborative environments, you'll find this position incredibly rewarding. Apply to join a forward-thinking team at AIT Global, Inc. and advance your career in data engineering.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

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.

Skills

Unity

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