Azure Databricks Engineer; Dallas, TX
Job in
Dallas, Dallas County, Texas, 75215, USA
Listed on 2026-01-12
Listing for:
Cedent
Full Time
position Listed on 2026-01-12
Job specializations:
-
IT/Tech
Data Engineer, Data Science Manager, Cloud Computing, Data Analyst
Job Description & How to Apply Below
- Design, build, and optimize scalable, high-performance data pipelines and data lakes using Azure Databricks.
- Architect and implement end-to-end analytics solutions leveraging Databricks and other Azure services (e.g., Azure Data Lake, Azure SQL, Azure Blob Storage).
- Lead the design of cloud-based architectures using Azure Databricks for data processing, transformation, and reporting.
- Design and implement ETL/ELT processes to ingest, process, and transform data across various sources (structured and unstructured).
- Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and develop data solutions.
- Manage data integration workflows between Databricks and other platforms like Power BI, Azure SQL, Synapse, etc.
- Optimization & Performance Tuning
:- Identify performance bottlenecks in Databricks environments and optimize clusters, queries, and code.
- Continuously improve and scale data pipelines to accommodate growing data volumes and business needs.
- Mentor and guide junior engineers and team members in best practices related to Azure Databricks and data engineering.
- Work closely with cross-functional teams (data science, analytics, business intelligence) to deliver integrated solutions.
- Provide technical leadership in cloud data architecture and data engineering.
- Monitoring & Security
:- Implement monitoring and alerting systems to ensure data pipelines and workflows are running smoothly.
- Ensure compliance with data security and governance standards across the data ecosystem.
- Stay up to date with the latest advancements in Azure Databricks, cloud technologies, and data engineering trends.
- Continuously evaluate and introduce new technologies and methodologies to enhance the data platform.
- Azure Databricks Architecture & Design
:- Design, build, and optimize scalable, high-performance data pipelines and data lakes using Azure Databricks.
- Architect and implement end-to-end analytics solutions leveraging Databricks and other Azure services (e.g., Azure Data Lake, Azure SQL, Azure Blob Storage).
- Lead the design of cloud-based architectures using Azure Databricks for data processing, transformation, and reporting.
- Data Engineering & Integration
:- Design and implement ETL/ELT processes to ingest, process, and transform data across various sources (structured and unstructured).
- Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and develop data solutions.
- Manage data integration workflows between Databricks and other platforms like Power BI, Azure SQL, Synapse, etc.
- Optimization & Performance Tuning
:- Identify performance bottlenecks in Databricks environments and optimize clusters, queries, and code.
- Continuously improve and scale data pipelines to accommodate growing data volumes and business needs.
- Collaboration & Leadership
:- Mentor and guide junior engineers and team members in best practices related to Azure Databricks and data engineering.
- Work closely with cross-functional teams (data science, analytics, business intelligence) to deliver integrated solutions.
- Provide technical leadership in cloud data architecture and data engineering.
- Monitoring & Security
:- Implement monitoring and alerting systems to ensure data pipelines and workflows are running smoothly.
- Ensure compliance with data security and governance standards across the data ecosystem.
- Continuous Improvement & Innovation
:- Stay up to date with the latest advancements in Azure Databricks, cloud technologies, and data engineering trends.
- Continuously evaluate and introduce new technologies and methodologies to enhance the data platform.
Skills and Qualifications
- Experience:
- Minimum 10 years of hands‑on experience in data engineering and cloud‑based data platforms.
- At least 5 years of experience working with Azure Databricks, building data pipelines, and performing data engineering tasks.
- Strong experience with Azure services such as Azure Data Lake, Azure Synapse Analytics, Azure Blob Storage, Azure SQL Database, etc.
- Technical
Skills:- Proficiency in Spark, PySpark, Scala, or SQL for large‑scale data processing.
- Expertise in Databricks notebooks, clusters, job…
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