Databricks Engineer
Posted 1 week ago by Daman Consulting
Negotiable
Undetermined
Remote
Remote
Summary: The Databricks Engineer is responsible for developing, maintaining, and optimizing big data solutions using the Databricks Unified Analytics Platform. This role supports data engineering, machine learning, and analytics initiatives within an organization that relies on large-scale data processing. The position requires collaboration with cross-functional teams and a focus on ensuring data quality, governance, and security. The role is a long-term contract with remote work, requiring occasional visits to the Austin office.
Key Responsibilities:
- Designing and developing scalable data pipelines
- Implementing ETL/ELT workflows
- Optimizing Spark jobs
- Integrating with Azure Data Factory
- Automating deployments
- Collaborating with cross-functional teams
- Ensuring data quality, governance, and security.
Key Skills:
- Implement ETL/ELT workflows for both structured and unstructured data
- Automate deployments using CI/CD tools
- Collaborate with cross-functional teams including data scientists, analysts, and stakeholders
- Design and maintain data models, schemas, and database structures to support analytical and operational use cases
- Evaluate and implement appropriate data storage solutions, including data lakes (Azure Data Lake Storage) and data warehouses
- Implement data validation and quality checks to ensure accuracy and consistency
- Contribute to data governance initiatives, including metadata management, data lineage, and data cataloging
- Implement data security measures, including encryption, access controls, and auditing; ensure compliance with regulations and best practices
- Proficiency in Python and R programming languages
- Strong SQL querying and data manipulation skills
- Experience with Azure cloud platform
- Experience with DevOps, CI/CD pipelines, and version control systems
- Working in agile, multicultural environments
- Strong troubleshooting and debugging capabilities
- Design and develop scalable data pipelines using Apache Spark on Databricks
- Optimize Spark jobs for performance and cost-efficiency
- Integrate Databricks solutions with cloud services (Azure Data Factory)
- Ensure data quality, governance, and security using Unity Catalog or Delta Lake
- Deep understanding of Apache Spark architecture, RDDs, DataFrames, and Spark SQL
- Hands-on experience with Databricks notebooks, clusters, jobs, and Delta Lake
- Knowledge of ML libraries (MLflow, Scikit-learn, TensorFlow)
- Databricks Certified Associate Developer for Apache Spark
- Azure Data Engineer Associate
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Detailed Description From Employer:
Duties include:
Job Title: Databricks Engineer (Big Data Engineer)
Job Location: Remote (Visit Austin office once a Month)
Job type: Long-term Contract
Job Description
The Worker is responsible for developing, maintaining, and optimizing big data solutions using the Databricks Unified Analytics Platform.
This role supports data engineering, machine learning, and analytics initiatives within this organization that relies on large-scale data processing.
This role supports data engineering, machine learning, and analytics initiatives within this organization that relies on large-scale data processing.
Duties include:
- Designing and developing scalable data pipelines
- Implementing ETL/ELT workflows
- Optimizing Spark jobs
- Integrating with Azure Data Factory
- Automating deployments
- Collaborating with cross-functional teams
- Ensuring data quality, governance, and security.
Required skills and qualifications
- Implement ETL/ELT workflows for both structured and unstructured data
- Automate deployments using CI/CD tools
- Collaborate with cross-functional teams including data scientists, analysts, and stakeholders
- Design and maintain data models, schemas, and database structures to support analytical and operational use cases
- Evaluate and implement appropriate data storage solutions, including data lakes (Azure Data Lake Storage) and data warehouses
- Implement data validation and quality checks to ensure accuracy and consistency
- Contribute to data governance initiatives, including metadata management, data lineage, and data cataloging
- Implement data security measures, including encryption, access controls, and auditing; ensure compliance with regulations and best practices
- Proficiency in Python and R programming languages
- Strong SQL querying and data manipulation skills
- Experience with Azure cloud platform
- Experience with DevOps, CI/CD pipelines, and version control systems
- Working in agile, multicultural environments
- Strong troubleshooting and debugging capabilities
- Design and develop scalable data pipelines using Apache Spark on Databricks
- Optimize Spark jobs for performance and cost-efficiency
- Integrate Databricks solutions with cloud services (Azure Data Factory)
- Ensure data quality, governance, and security using Unity Catalog or Delta Lake
- Deep understanding of Apache Spark architecture, RDDs, DataFrames, and Spark SQL
- Hands-on experience with Databricks notebooks, clusters, jobs, and Delta Lake
- Knowledge of ML libraries (MLflow, Scikit-learn, TensorFlow)
- Databricks Certified Associate Developer for Apache Spark
- Azure Data Engineer Associate