Urgent Need – Databricks Engineer – Los Angeles, CA preferred / Remote

Title: Databricks Engineer
Work Location: Remote 

MUST HAVE MEDIA / Entertainment Domain Candidates

Skills – Databricks, Spark, Python, AWS, SQL

Key Responsibilities

Data Pipeline Development: Design and implement robust ETL/ELT pipelines using Databricks, PySpark, and Delta Lake to process structured and unstructured data efficiently.
Performance Optimization: Tune and optimize Databricks clusters and notebooks for performance, scalability, and cost-efficiency.
Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions that meet business needs.
Cloud Integration: Leverage cloud platforms (AWS, Azure, GCP) to build and deploy data solutions, ensuring seamless integration with existing infrastructure.
Data Modeling: Develop and maintain data models that support analytics and machine learning workflows.
Automation & Monitoring: Implement automated testing, monitoring, and alerting mechanisms to ensure data pipeline reliability and data quality.
Documentation & Best Practices: Maintain comprehensive documentation of data workflows and adhere to best practices in coding, version control, and data governance.
 

Required Qualifications

Experience: 5+ years in data engineering, with hands-on experience using Databricks and Apache Spark.
Programming Skills: Proficiency in Python and SQL; experience with Scala is a plus.
Cloud Platforms: Strong experience with cloud services such as AWS (e.g., S3, Glue, Redshift), Azure (e.g., Data Factory, Synapse), or GCP.
Data Engineering Tools: Familiarity with tools like Airflow, Kafka, and dbt.
Data Modeling: Experience in designing data models for analytics and machine learning applications.
Collaboration: Proven ability to work in cross-functional teams and communicate effectively with non-technical stakeholders.
 

Primary Skill Set

Databricks, Apache Spark, Python, SQL, Scala (optional), ETL/ELT development, Delta Lake, Cloud platforms (AWS, Azure, GCP), Data modeling, Cross-functional collaboration, Communication

Secondary Skill Set

Airflow, dbt, Kafka, Hadoop, MLflow, Unity Catalog, Delta Live Tables, Cluster optimization, Data governance, Security and compliance, Databricks certifications