Company
Technology
SeniorDatabricksDataEngineer(AWS)
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Databricks Data Engineer (AWS). Design ETL/ELT pipelines. Develop ETL/ELT pipelines”
Industry & Context.
Performance tuning; Troubleshooting; Optimization
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field, Minimum 8 years of experience in cloud data engineering, data architecture, or platform development, At least 3 years of hands-on experience working with Databricks in production environments, Expertise in building and maintaining large-scale ETL/ELT pipelines, Expertise in cloud-native data architectures, Deep experience with AWS services, Programming skills in SQL and Python, Proven experience implementing data governance, Proven experience implementing security controls, Proven experience implementing high-quality data management practices, Experience working with data lakes, Experience working with data warehouses, Experience working with modern analytics platforms, Familiarity with performance tuning, Familiarity with troubleshooting, Familiarity with optimization in distributed data environments
Nice to Have
Databricks Data Engineer certification, AWS Data Analytics Specialty certification, Exposure to regulated environments, Familiarity with compliance frameworks
What You'll Do.
Design ETL/ELT pipelines
Develop ETL/ELT pipelines
Maintain ETL/ELT pipelines
Implement Lakehouse components
Optimize Lakehouse components
Maintain data products
Develop medallion architecture
Enforce metadata management
Enforce governance standards
Optimize data processing
Collaborate with teams
Support architecture reviews
Support platform modernization
Support continuous improvement
How You'll Work.
Team & Collaboration
Cross-functional teams; Cloud engineers; Security specialists; Business stakeholders
Full Job Description
## Accountabilities Design, develop, and maintain scalable ETL/ELT pipelines and data workflows using Databricks and Amazon Web Services (AWS), ensuring reliability and performance at enterprise scale. Implement and optimize Lakehouse components such as Delta Lake, Unity Catalog, Auto Loader, Delta Live Tables, Databricks SQL, and Delta Sharing to enable governed data access and analytics. Build and maintain data models and governed data products supporting analytics, reporting, and machine learning workloads across the organization. Develop medallion architecture pipelines and enforce enterprise data quality, lineage, metadata management, and governance standards. Optimize data processing performance through partitioning strategies, query tuning, caching, and workload optimization techniques. Collaborate with cross-functional teams including cloud engineers, security specialists, and business stakeholders to deliver secure, production-ready data solutions. Support architecture reviews, platform modernization initiatives, and continuous improvement efforts across the enterprise data ecosystem. Requirements: Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field. Minimum 8 years of experience in cloud data engineering, data architecture, or platform development roles. At least 3 years of hands-on experience working with Databricks in production environments. Strong expertise in building and maintaining large-scale ETL/ELT pipelines and cloud-native data architectures. Deep experience with AWS services such as S3, Glue, Athena, Lambda, Redshift, IAM, and CloudWatch. Strong programming skills in SQL and Python for data engineering and transformation tasks. Proven experience implementing data governance, security controls, and high-quality data management practices. Experience working with data lakes, data warehouses, and modern analytics platforms. Familiarity with performance tuning, troubleshooting, and optimization i
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